Relevant bibliographies by topics / Image partition

Academic literature on the topic 'Image partition'

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Published: 10 March 2023
Last updated: 11 March 2023

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Journal articles on the topic "Image partition"

1

Wang, Lei, Bo Yu, Fang Chen, Congrong Li, Bin Li, and Ning Wang. "A Cluster-Based Partition Method of Remote Sensing Data for Efficient Distributed Image Processing." Remote Sensing 14, no. 19 (October 5, 2022): 4964. http://dx.doi.org/10.3390/rs14194964.

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Data stream partitioning is a fundamental and important mechanism for distributed systems. However, use of an inappropriate partition scheme may generate a data skew problem, which can influence the execution efficiency of many application tasks. Processing of skewed partitions usually takes a longer time, need more computational resources to complete the task and can even become a performance bottleneck. To solve such data skew issues, this paper proposes a novel partition method to divide on demand the image tiles uniformly into partitions. The partitioning problem is then transformed into a uniform and compact clustering problem whereby the image tiles are regarded as image pixels without spectrum and texture information. First, the equal area conversion principle was used to select the seed points of the partitions and then the image tiles were aggregated in an image layout, thus achieving an initial partition scheme. Second, the image tiles of the initial partition were finely adjusted in the vertical and horizontal directions in separate steps to achieve a uniform distribution among the partitions. Two traditional partition methods were adopted to evaluate the efficiency of the proposed method in terms of the image segmentation testing, data shuffle testing, and image clipping testing. The results demonstrated that the proposed partition method solved the data skew problem observed in the hash partition method. In addition, this method is designed specifically for processing of image tiles and makes the related processing operations for large-scale images faster and more efficient.
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Jung, Ho Yub, and Kyoung Mu Lee. "Image Segmentation by Edge Partitioning over a Nonsubmodular Markov Random Field." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/683176.

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Edge weight-based segmentation methods, such as normalized cut or minimum cut, require a partition number specification for their energy formulation. The number of partitions plays an important role in the segmentation overall quality. However, finding a suitable partition number is a nontrivial problem, and the numbers are ordinarily manually assigned. This is an aspect of the general partition problem, where finding the partition number is an important and difficult issue. In this paper, the edge weights instead of the pixels are partitioned to segment the images. By partitioning the edge weights into two disjoints sets, that is, cut and connect, an image can be partitioned into all possible disjointed segments. The proposed energy function is independent of the number of segments. The energy is minimized by iterating the QPBO-α-expansion algorithm over the pairwise Markov random field and the mean estimation of the cut and connected edges. Experiments using the Berkeley database show that the proposed segmentation method can obtain equivalently accurate segmentation results without designating the segmentation numbers.
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Zuo, Yong Xia, Guo Qiang Wang, and Chun Cheng Zuo. "The Segmentation Algorithm for Pavement Cracking Images Based on the Improved Fuzzy Clustering." Applied Mechanics and Materials 319 (May 2013): 362–66. http://dx.doi.org/10.4028/www.scientific.net/amm.319.362.

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The segmentation technology of pavement cracking image is critical for identifying, quantifying and classifying pavement cracks. An improved fuzzy clustering algorithm is introduced to segment pavement cracking images. The algorithm makes no assumptions the initial position of clusters. For each value of the multiscale parameter, it obtains a corresponding hard partition. The different partitions values of the multiscale parameter indicate the structure of the image in different partitional scales. The algorithm was tested on actual pavement cracking images. We compared the results with FCM and OTSU to show that the improved fuzzy clustering algorithm can provide better crack edges.
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Liang, Dong, Rui Wang, Xiaowei Tian, and Cong Zou. "PCGAN: Partition-Controlled Human Image Generation." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8698–705. http://dx.doi.org/10.1609/aaai.v33i01.33018698.

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Human image generation is a very challenging task since it is affected by many factors. Many human image generation methods focus on generating human images conditioned on a given pose, while the generated backgrounds are often blurred. In this paper, we propose a novel Partition-Controlled GAN to generate human images according to target pose and background. Firstly, human poses in the given images are extracted, and foreground/background are partitioned for further use. Secondly, we extract and fuse appearance features, pose features and background features to generate the desired images. Experiments on Market-1501 and DeepFashion datasets show that our model not only generates realistic human images but also produce the human pose and background as we want. Extensive experiments on COCO and LIP datasets indicate the potential of our method.
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Alameddine, Jihan, Kacem Chehdi, and Claude Cariou. "Hierarchical Unsupervised Partitioning of Large Size Data and Its Application to Hyperspectral Images." Remote Sensing 13, no. 23 (November 30, 2021): 4874. http://dx.doi.org/10.3390/rs13234874.

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In this paper, we propose a true unsupervised method to partition large-size images, where the number of classes, training samples, and other a priori information is not known. Thus, partitioning an image without any knowledge is a great challenge. This novel adaptive and hierarchical classification method is based on affinity propagation, where all criteria and parameters are adaptively calculated from the image to be partitioned. It is reliable to objectively discover classes of an image without user intervention and therefore satisfies all the objectives of an unsupervised method. Hierarchical partitioning adopted allows the user to analyze and interpret the data very finely. The optimal partition maximizing an objective criterion provides the number of classes and the exemplar of each class. The efficiency of the proposed method is demonstrated through experimental results on hyperspectral images. The obtained results show its superiority over the most widely used unsupervised and semi-supervised methods. The developed method can be used in several application domains to partition large-size images or data. It allows the user to consider all or part of the obtained classes and gives the possibility to select the samples in an objective way during a learning process.
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Yao, Hongtai, Xianpei Wang, Le Zhao, Meng Tian, Zini Jian, Li Gong, and Bowen Li. "An Object-Based Markov Random Field with Partition-Global Alternately Updated for Semantic Segmentation of High Spatial Resolution Remote Sensing Image." Remote Sensing 14, no. 1 (December 29, 2021): 127. http://dx.doi.org/10.3390/rs14010127.

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The Markov random field (MRF) method is widely used in remote sensing image semantic segmentation because of its excellent spatial (relationship description) ability. However, there are some targets that are relatively small and sparsely distributed in the entire image, which makes it easy to misclassify these pixels into different classes. To solve this problem, this paper proposes an object-based Markov random field method with partition-global alternately updated (OMRF-PGAU). First, four partition images are constructed based on the original image, they overlap with each other and can be reconstructed into the original image; the number of categories and region granularity for these partition images are set. Then, the MRF model is built on the partition images and the original image, their segmentations are alternately updated. The update path adopts a circular path, and the correlation assumption is adopted to establish the connection between the label fields of partition images and the original image. Finally, the relationship between each label field is constantly updated, and the final segmentation result is output after the segmentation has converged. Experiments on texture images and different remote sensing image datasets show that the proposed OMRF-PGAU algorithm has a better segmentation performance than other selected state-of-the-art MRF-based methods.
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Lin, Cheng-Shian, Chien-Chang Chen, and Yu-Cheng Chen. "XOR-Based Progressively Secret Image Sharing." Mathematics 9, no. 6 (March 12, 2021): 612. http://dx.doi.org/10.3390/math9060612.

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Secret image sharing technology is a strategy for jointly protecting secret images. The (n, n) secret image sharing problem can be solved by conventional Boolean calculation easily. However, how to recover secret images with progressive steps is not addressed. In this study, we proposed an XOR-based (m, t, Ti) multi-secret image sharing scheme that shares m secret images among m participants and recovers m shared images progressively with t thresholds. The proposed secret images partition strategy (SIPS) partitions m secret images to generate intermediate images for different thresholds in the sharing procedure. Based on progressive recovery property, the proposed recovery method recovers parts of the secret images by gathering consecutive shared images. Moreover, gathering all shared images can perfectly recover all secret images. The experimental results show that the proposed XOR-based multi-secret image sharing method has high security and efficiency.
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Gondimalla, Ashish, Jianqiao Liu, Mithuna Thottethodi, and T. N. Vijaykumar. "Occam: Optimal Data Reuse for Convolutional Neural Networks." ACM Transactions on Architecture and Code Optimization 20, no. 1 (December 16, 2022): 1–25. http://dx.doi.org/10.1145/3566052.

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Convolutional neural networks (CNNs) are emerging as powerful tools for image processing in important commercial applications. We focus on the important problem of improving the latency of image recognition. While CNNs are highly amenable to prefetching and multithreading to avoid memory latency issues, CNNs’ large data – each layer’s input, filters, and output – poses a memory bandwidth problem. While previous work captures only some of the enormous data reuse, full reuse implies that the initial input image and filters are read once from off-chip and the final output is written once off-chip without spilling the intermediate layers’ data to off-chip. We propose Occam to capture full reuse via four contributions. First, we identify the necessary conditions for full reuse. Second, we identify the dependence closure as the sufficient condition to capture full reuse using the least on-chip memory. Third, because the dependence closure is often too large to fit in on-chip memory, we propose a dynamic programming algorithm that optimally partitions a given CNN to guarantee the least off-chip traffic at the partition boundaries for a given on-chip capacity. While tiling is well-known, our contribution determines the optimal cross-layer tiles. Occam’s partitions reside on different chips, forming a pipeline so that a partition’s filters and dependence closure remain on-chip as different images pass through (i.e., each partition incurs off-chip traffic only for its inputs and outputs). Finally, because the optimal partitions may result in an unbalanced pipeline, we propose staggered asynchronous pipelines (STAPs) that replicate bottleneck stages to improve throughput by staggering mini-batches across replicas. Importantly, STAPs achieve balanced pipelines without changing Occam’s optimal partitioning. Our simulations show that, on average, Occam cuts off-chip transfers by 21× and achieves 2.04× and 1.21× better performance, and 33% better energy than the base case, respectively. Using a field-programmable gate array (FPGA) implementation, Occam performs 6.1× and 1.5× better, on average, than the base case and Layer Fusion, respectively.
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Wei, Yuan, and Kin Tak U. "A Novel Non-Uniform BTC and its Application." Applied Mechanics and Materials 590 (June 2014): 789–94. http://dx.doi.org/10.4028/www.scientific.net/amm.590.789.

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In this paper, a novel image representation coding based on non-uniform Block Truncation Coding (BTC) is proposed. A given image can automatically be partitioned into different regions with different sizes and the bivariate piecewise polynomials are used to do the Least Square Approximation for the pixel values in each sub-region based on BTC bitmap. When the approximation error and initial partition are specified, a specific image partition result is obtained. The image re-construction quality of the proposed algorithm is better than that of the traditional BTC. Based on this algorithm, an effective denoising scheme of image is implemented and some of the experimental examples are illustrated to prove that the quality of the re-constructed image, the denoising effect are all satisfactory and can be referenced by other researchers.
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Hindman, Neil, and Imre Leader. "Image Partition Regularity of Matrices." Combinatorics, Probability and Computing 2, no. 4 (December 1993): 437–63. http://dx.doi.org/10.1017/s0963548300000821.

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Many of the classical results of Ramsey Theory, including those of Hilbert, Schur, and van der Waerden, are naturally stated as instances of the following problem: given a u × ν matrix A with rational entries, is it true, that whenever the set ℕ of positive integers is finitely coloured, there must exist some x∈ℕν such that all entries of Ax are the same colour? While the theorems cited are all consequences of Rado's theorem, the general problem had remained open. We provide here several solutions for the alternate problem, which asks that x∈ℕν. Based on this, we solve the general problem, giving various equivalent characterizations.
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Dissertations / Theses on the topic "Image partition"

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Bernat, Andrew. "Which partition scheme for what image?, partitioned iterated function systems for fractal image compression." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2002. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ65602.pdf.

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Lu, Huihai. "Evolutionary image analysis in binary partition trees." Thesis, University of Essex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438156.

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Valero, Valbuena Silvia. "Hyperspectral image representation and processing with binary partition trees." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/130832.

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The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. Therefore, under the title Hyperspectral image representation and Processing with Binary Partition Trees, this PhD thesis proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation: the Binary Partition Tree (BPT). This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure. Hence, the Binary Partition Tree succeeds in presenting: (i) the decomposition of the image in terms of coherent regions and (ii) the inclusion relations of the regions in the scene. Based on region-merging techniques, the construction of BPT is investigated in this work by studying hyperspectral region models and the associated similarity metrics. As a matter of fact, the very high dimensionality and the complexity of the data require the definition of specific region models and similarity measures. Once the BPT is constructed, the fixed tree structure allows implementing efficient and advanced application-dependent techniques on it. The application-dependent processing of BPT is generally implemented through a specific pruning of the tree. Accordingly, some pruning techniques are proposed and discussed according to different applications. This Ph.D is focused in particular on segmentation, object detection and classification of hyperspectral imagery. Experimental results on various hyperspectral data sets demonstrate the interest and the good performances of the BPT representation
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Zhao, Mansuo. "Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization." University of Sydney. School of Electrical and Information Engineering, 2005. http://hdl.handle.net/2123/699.

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Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits the geometric features of blueprint images. This is implemented by utilizing a robust windows operation, which is based on the assumption that the objects have "e;C"e; shape in a small area. We make use of multiple window sizes in the windows operation. This not only reduces computation time but also separates effectively thin lines from wide lines. Our method can automatically determine the threshold of images. Experiments show that our method is effective for blueprint images and achieves good results over a wide range of images. Second, the fuzzy set theory, along with probability partition and maximum entropy theory, is explored to compute the threshold based on the histogram of the image. Fuzzy set theory has been widely used in many fields where the ambiguous phenomena exist since it was proposed by Zadeh in 1965. And many thresholding methods have also been developed by using this theory. The concept we are using here is called fuzzy partition. Fuzzy partition means that a histogram is parted into several groups by some fuzzy sets which represent the fuzzy membership of each group because our method is based on histogram of the image . Probability partition is associated with fuzzy partition. The probability distribution of each group is derived from the fuzzy partition. Entropy which originates from thermodynamic theory is introduced into communications theory as a commonly used criteria to measure the information transmitted through a channel. It is adopted by image processing as a measurement of the information contained in the processed images. Thus it is applied in our method as a criterion for selecting the optimal fuzzy sets which partition the histogram. To find the threshold, the histogram of the image is partitioned by fuzzy sets which satisfy a certain entropy restriction. The search for the best possible fuzzy sets becomes an important issue. There is no efficient method for the searching procedure. Therefore, expansion to multiple level thresholding with fuzzy partition becomes extremely time consuming or even impossible. In this thesis, the relationship between a probability partition (PP) and a fuzzy C-partition (FP) is studied. This relationship and the entropy approach are used to derive a thresholding technique to select the optimal fuzzy C-partition. The measure of the selection quality is the entropy function defined by the PP and FP. A necessary condition of the entropy function arriving at a maximum is derived. Based on this condition, an efficient search procedure for two-level thresholding is derived, which makes the search so efficient that extension to multilevel thresholding becomes possible. A novel fuzzy membership function is proposed in three-level thresholding which produces a better result because a new relationship among the fuzzy membership functions is presented. This new relationship gives more flexibility in the search for the optimal fuzzy sets, although it also increases the complication in the search for the fuzzy sets in multi-level thresholding. This complication is solved by a new method called the "e;Onion-Peeling"e; method. Because the relationship between the fuzzy membership functions is so complicated it is impossible to obtain the membership functions all at once. The search procedure is decomposed into several layers of three-level partitions except for the last layer which may be a two-level one. So the big problem is simplified to three-level partitions such that we can obtain the two outmost membership functions without worrying too much about the complicated intersections among the membership functions. The method is further revised for images with a dominant area of background or an object which affects the appearance of the histogram of the image. The histogram is the basis of our method as well as of many other methods. A "e;bad"e; shape of the histogram will result in a bad thresholded image. A quadtree scheme is adopted to decompose the image into homogeneous areas and heterogeneous areas. And a multi-resolution thresholding method based on quadtree and fuzzy partition is then devised to deal with these images. Extension of fuzzy partition methods to color images is also examined. An adaptive thresholding method for color images based on fuzzy partition is proposed which can determine the number of thresholding levels automatically. This thesis concludes that the "e;C"e; shape assumption and varying sizes of windows for windows operation contribute to a better segmentation of the blueprint images. The efficient search procedure for the optimal fuzzy sets in the fuzzy-2 partition of the histogram of the image accelerates the process so much that it enables the extension of it to multilevel thresholding. In three-level fuzzy partition the new relationship presentation among the three fuzzy membership functions makes more sense than the conventional assumption and, as a result, performs better. A novel method, the "e;Onion-Peeling"e; method, is devised for dealing with the complexity at the intersection among the multiple membership functions in the multilevel fuzzy partition. It decomposes the multilevel partition into the fuzzy-3 partitions and the fuzzy-2 partitions by transposing the partition space in the histogram. Thus it is efficient in multilevel thresholding. A multi-resolution method which applies the quadtree scheme to distinguish the heterogeneous areas from the homogeneous areas is designed for the images with large homogeneous areas which usually distorts the histogram of the image. The new histogram based on only the heterogeneous area is adopted for partition and outperforms the old one. While validity checks filter out the fragmented points which are only a small portion of the whole image. Thus it gives good thresholded images for human face images.
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Zhao, Mansuo. "Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization." Thesis, The University of Sydney, 2004. http://hdl.handle.net/2123/699.

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Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits the geometric features of blueprint images. This is implemented by utilizing a robust windows operation, which is based on the assumption that the objects have "e;C"e; shape in a small area. We make use of multiple window sizes in the windows operation. This not only reduces computation time but also separates effectively thin lines from wide lines. Our method can automatically determine the threshold of images. Experiments show that our method is effective for blueprint images and achieves good results over a wide range of images. Second, the fuzzy set theory, along with probability partition and maximum entropy theory, is explored to compute the threshold based on the histogram of the image. Fuzzy set theory has been widely used in many fields where the ambiguous phenomena exist since it was proposed by Zadeh in 1965. And many thresholding methods have also been developed by using this theory. The concept we are using here is called fuzzy partition. Fuzzy partition means that a histogram is parted into several groups by some fuzzy sets which represent the fuzzy membership of each group because our method is based on histogram of the image . Probability partition is associated with fuzzy partition. The probability distribution of each group is derived from the fuzzy partition. Entropy which originates from thermodynamic theory is introduced into communications theory as a commonly used criteria to measure the information transmitted through a channel. It is adopted by image processing as a measurement of the information contained in the processed images. Thus it is applied in our method as a criterion for selecting the optimal fuzzy sets which partition the histogram. To find the threshold, the histogram of the image is partitioned by fuzzy sets which satisfy a certain entropy restriction. The search for the best possible fuzzy sets becomes an important issue. There is no efficient method for the searching procedure. Therefore, expansion to multiple level thresholding with fuzzy partition becomes extremely time consuming or even impossible. In this thesis, the relationship between a probability partition (PP) and a fuzzy C-partition (FP) is studied. This relationship and the entropy approach are used to derive a thresholding technique to select the optimal fuzzy C-partition. The measure of the selection quality is the entropy function defined by the PP and FP. A necessary condition of the entropy function arriving at a maximum is derived. Based on this condition, an efficient search procedure for two-level thresholding is derived, which makes the search so efficient that extension to multilevel thresholding becomes possible. A novel fuzzy membership function is proposed in three-level thresholding which produces a better result because a new relationship among the fuzzy membership functions is presented. This new relationship gives more flexibility in the search for the optimal fuzzy sets, although it also increases the complication in the search for the fuzzy sets in multi-level thresholding. This complication is solved by a new method called the "e;Onion-Peeling"e; method. Because the relationship between the fuzzy membership functions is so complicated it is impossible to obtain the membership functions all at once. The search procedure is decomposed into several layers of three-level partitions except for the last layer which may be a two-level one. So the big problem is simplified to three-level partitions such that we can obtain the two outmost membership functions without worrying too much about the complicated intersections among the membership functions. The method is further revised for images with a dominant area of background or an object which affects the appearance of the histogram of the image. The histogram is the basis of our method as well as of many other methods. A "e;bad"e; shape of the histogram will result in a bad thresholded image. A quadtree scheme is adopted to decompose the image into homogeneous areas and heterogeneous areas. And a multi-resolution thresholding method based on quadtree and fuzzy partition is then devised to deal with these images. Extension of fuzzy partition methods to color images is also examined. An adaptive thresholding method for color images based on fuzzy partition is proposed which can determine the number of thresholding levels automatically. This thesis concludes that the "e;C"e; shape assumption and varying sizes of windows for windows operation contribute to a better segmentation of the blueprint images. The efficient search procedure for the optimal fuzzy sets in the fuzzy-2 partition of the histogram of the image accelerates the process so much that it enables the extension of it to multilevel thresholding. In three-level fuzzy partition the new relationship presentation among the three fuzzy membership functions makes more sense than the conventional assumption and, as a result, performs better. A novel method, the "e;Onion-Peeling"e; method, is devised for dealing with the complexity at the intersection among the multiple membership functions in the multilevel fuzzy partition. It decomposes the multilevel partition into the fuzzy-3 partitions and the fuzzy-2 partitions by transposing the partition space in the histogram. Thus it is efficient in multilevel thresholding. A multi-resolution method which applies the quadtree scheme to distinguish the heterogeneous areas from the homogeneous areas is designed for the images with large homogeneous areas which usually distorts the histogram of the image. The new histogram based on only the heterogeneous area is adopted for partition and outperforms the old one. While validity checks filter out the fragmented points which are only a small portion of the whole image. Thus it gives good thresholded images for human face images.
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Cutolo, Alfredo. "Image partition and video segmentation using the Mumford-Shah functional." Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/280.

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2010 - 2011
The aim of this Thesis is to present an image partition and video segmentation procedure, based on the minimization of a modified version of Mumford-Shah functional. The Mumford-Shah functional used for image partition has been then extended to develop a video segmentation procedure. Differently by the image processing, in video analysis besides the usual spatial connectivity of pixels (or regions) on each single frame, we have a natural notion of “temporal” connectivity between pixels (or regions) on consecutive frames given by the optical flow. In this case, it makes sense to extend the tree data structure used to model a single image with a graph data structure that allows to handle a video sequence. The video segmentation procedure is based on minimization of a modified version of a Mumford-Shah functional. In particular the functional used for image partition allows to merge neighboring regions with similar color without considering their movement. Our idea has been to merge neighboring regions with similar color and similar optical flow vector. Also in this case the minimization of Mumford-Shah functional can be very complex if we consider each possible combination of the graph nodes. This computation becomes easy to do if we take into account a hierarchy of partitions constructed starting by the nodes of the graph.[edited by author]
X n.s.
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Sudirman. "Colour image coding indexing and retrieval using binary space partition tree." Thesis, University of Nottingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275171.

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Berry, Dominic William. "Adaptive phase measurements /." [St. Lucia, Qld.], 2002. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16247.pdf.

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Kim, Il-Ryeol. "Wavelet domain partition-based signal processing with applications to image denoising and compression." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 2.98 Mb., 119 p, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3221054.

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Gomila, Cristina. "Mise en correspondance de partitions en vue du suivi d'objets." Phd thesis, École Nationale Supérieure des Mines de Paris, 2001. http://pastel.archives-ouvertes.fr/pastel-00003272.

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Dans le domaine des applications multimédia, les futurs standards vont permettre de créer de nouvelles voies de communication, d'accès et de manipulation de l'information audiovisuelle qui vont bien au-delà de la simple compression à laquelle se limitaient les standards de codage précédents. Parmi les nouvelles fonctionnalités, il est espéré que l'utilisateur pourra avoir accès au contenu des images par édition et manipulation des objets présents. Néanmoins, la standardisation ne couvre que la représentation et le codage de ces objets, en laissant ouvert un large champ de développement pour ce qui concerne la probl ématique liée à leur extraction et à leur suivi lorsqu'ils évoluent au long d'une séquence vidéo. C'est précisément sur ce point que porte cette thèse. Dans un premier temps, nous avons procédé à l' étude et à la mise au point d'algorithmes de filtrage et de segmentation à caractère générique, car ces outils sont à la base de tout système d'analyse du contenu d'une image ou d'une séquence. Plus concr ètement, nous avons étudié en détail une nouvelle classe de filtres morphologiques connus sous le nom de nivellements ainsi qu'une variation des algorithmes de segmentation basée sur l'inondation contrainte d'une image gradient. Les techniques de segmentation ont pour but de produire une partition de l'image aussi proche que possible de celle faite par l' oeil humain, en vue de la reconnaissance postérieure des objets. Néanmoins, dans la plupart des cas, cette dernière tâche ne peut être faite que par interaction humaine et, pourtant, lorsqu'on veut retrouver un objet dans une large collection d'images, ou suivre son évolution au long d'une s équence, la surveillance de chacune des partitions devient impossible. S'impose alors le développement d'algorithmes de mise en correspondance capables de propager l'information dans une série d'images, en limitant l'interaction humaine à une seule étape d'initialisation. En faisant le passage des images fixes aux séquences, la partie centrale de cette thèse est consacrée à l' étude du problème de la mise en correspondance de partitions. La méthode que nous avons développée, nommée technique de Segmentation et Appariement Conjoint (SAC), peut être définie comme étant de nature hybride. Elle combine des algorithmes classiques de mise en correspondance de graphes avec de nouvelles techniques d' édition, basées sur les hiérarchies de partitions fournies par la segmentation morphologique. Cette combinaison a donné lieu à un algorithme très robuste, malgré l'instabilité typiquement associée aux processus de segmentation. La segmentation de deux images peut différer fortement si on la considère du seul point de vue d'une partition unique ; néanmoins nous avons montré qu'elle est beaucoup plus stable si on considère des hiérarchies de partitions emboîtées, dans lesquelles tous les contours présents apparaissent, chacun avec une valuation indiquant sa force. Les résultats obtenus par la technique SAC ont fait d'elle une approche très prometteuse. Souple et puissante, elle est capable de reconnaître un objet lorsqu'il réapparaît après occultation grâce à la gestion d'un graphe de mémoire. Bien que nous nous soyons int éressés tout particulièrement à la problématique du suivi, les algorithmes mis au point ont un champ d'application beaucoup plus vaste dans le domaine de l'indexation, en particulier pour la recherche d'objets dans une base de données d'images ou de séquences. Finalement, dans le cadre du projet européen M4M (MPEG f(o)ur mobiles) nous avons abordé la mise en oeuvre d'un démonstrateur de segmentation en temps réel capable de détecter, segmenter et suivre un personnage dans des séquences de vidéophonie. Dans le cadre de cette application, la contrainte du temps réel est devenue le grand d éfi à surmonter, en nous obligeant a simplifier et à optimiser nos algorithmes. L'int erêt principal en termes des nouveaux services est double : d'un côté le détourage automatique du locuteur permettrait d'adapter le codage à l'objet, économisant du débit sans perte de qualité sur les régions d'int erêt ; d'un autre côté il permettrait de faire l' édition personnalisée des séquences en changeant la composition de la scène, par exemple en introduisant un nouveau fond, ou en disposant plusieurs locuteurs dans une salle de conférence virtuelle.
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Books on the topic "Image partition"

1

Pearlman, William A., and Amir Said. Set Partition Coding: Part I of Set Partition Coding and Image Wavelet Coding Systems. Now Publishers, 2008.

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Pearlman, William A., and Amir Said. Image Wavelet Coding Systems: Part II of Set Partition Coding and Image Wavelet Coding Systems. Now Publishers, 2008.

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Grene, Nicholas. Farming in Modern Irish Literature. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198861294.001.0001.

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This innovative study analyzes the range of representation of farming in Irish literature in the period since independence/partition in 1922, as Ireland moved from a largely agricultural to a developed urban society. In many different forms, poetry, drama, fiction, and autobiography, writers have made literary capital by looking back at their rural backgrounds, even where those may be a generation back. The first five chapters examine some of the key themes: the impact of inheritance on family, in the patriarchal system where there could only be one male heir; the struggles for survival in the poorest regions of the West of Ireland; the uses of childhood farming memories whether idyllic or traumatic; the representation of communities, challenging the homogeneous idealizing images of the Literary Revival; the impact of modernization on successive generations into the twenty-first century. The final three chapters are devoted to three major writers in whose work farming is central: Patrick Kavanagh, the small farmer who had to find an individual voice to express his own unique experience; John McGahern in whose fiction the life of the farm is always posited as alternative to an arid and rootless urban milieu; Seamus Heaney who re-imagined his farming childhood in so many different modes throughout his career.
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Book chapters on the topic "Image partition"

1

Pearlman, William A. "Set Partition Embedded Block (SPECK) Coding." In Wavelet Image Compression, 23–45. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-031-02248-7_5.

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Fernandez, Gregory, and Chabane Djeraba. "Partition Cardinality Estimation in Image Repositories." In Mining Multimedia and Complex Data, 232–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39666-6_15.

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Lee, David C., Qifa Ke, and Michael Isard. "Partition Min-Hash for Partial Duplicate Image Discovery." In Computer Vision – ECCV 2010, 648–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15549-9_47.

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Brémond, R., and F. Marqués. "Segmentation-Based Morphological Interpolation of Partition Sequences." In Mathematical Morphology and its Applications to Image and Signal Processing, 369–76. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0469-2_43.

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Ouzounis, Georgios K., and Pierre Soille. "Pattern Spectra from Partition Pyramids and Hierarchies." In Mathematical Morphology and Its Applications to Image and Signal Processing, 108–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21569-8_10.

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Yang, Yuting, and Houliang Kang. "A Novel Algorithm of Contour Tracking and Partition for Dongba Hieroglyph." In Image and Graphics Technologies and Applications, 157–67. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1702-6_16.

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Song, Chang, Yifeng Zhang, and Guojun Lu. "Reversible Data Hiding in Encrypted Images Based on Image Partition and Spatial Correlation." In Digital Forensics and Watermarking, 180–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11389-6_14.

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Marie-Julie, Jean Michel, and Hassane Essafi. "Image indexing by using a rotation and scale invariant partition." In Multimedia Applications, Services and Techniques — ECMAST'98, 163–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64594-2_93.

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Zhang, Mengmeng, Aibin Huang, Ruyu Zhai, and Saqing Wang. "Adaptive Partition Total Variation Algorithm for Medical Ultrasound Image Denoising." In Lecture Notes in Electrical Engineering, 105–12. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1673-1_18.

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Vega-Pons, Sandro, and José Ruiz-Shulcloper. "Partition Selection Approach for Hierarchical Clustering Based on Clustering Ensemble." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 525–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16687-7_69.

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Conference papers on the topic "Image partition"

1

Ausbeck, Jr., Paul J. "Image partition boundary coding." In SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, edited by Andrew G. Tescher. SPIE, 1998. http://dx.doi.org/10.1117/12.323195.

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Salembier, Philippe. "Motion-compensated partition coding." In Visual Communications and Image Processing '96, edited by Rashid Ansari and Mark J. T. Smith. SPIE, 1996. http://dx.doi.org/10.1117/12.233255.

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Zhang, Daming, Maosheng Fu, Dengdi Sun, and Bin Luo. "Image threshold selection with Isoperimetric partition." In Education (ICCSE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccse.2010.5593621.

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Jiang Ke and Wang Jing-jing. "Web-based Image Scale dynamic partition." In 2010 IEEE 11th International Conference on Computer-Aided Industrial Design & Conceptual Design 1. IEEE, 2010. http://dx.doi.org/10.1109/caidcd.2010.5681335.

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Hung, Edson M., Ricardo L. De Queiroz, and Debargha Mukherjee. "On Macroblock Partition for Motion Compensation." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.312686.

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Guan, Mingyang, Changyun Wen, Kwang-Yong Lim, Mao Shan, Paul Tan, Cheng-Leong Ng, and Ying Zou. "Visual tracking via random partition image hashing." In 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2016. http://dx.doi.org/10.1109/icarcv.2016.7838673.

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Valero, Silvia, Philippe Salembier, and Jocelyn Chanussot. "Hyperspectral image segmentation using Binary Partition Trees." In 2011 18th IEEE International Conference on Image Processing (ICIP 2011). IEEE, 2011. http://dx.doi.org/10.1109/icip.2011.6115666.

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Pirnog, Ionut, Cristina Oprea, Constantin Paleologu, and Dragos Nicolae Vizireanu. "Improved Minkowsky Metric for Image Region Partition." In 2008 3rd International Multi-Conference on Computing in the Global Information Thechnology (ICCGI). IEEE, 2008. http://dx.doi.org/10.1109/iccgi.2008.41.

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He, Guanghui, Yuanyan Tang, Bin Fang, and Taiping Zhang. "Weightiness image partition in 3D face recognition." In 2009 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2009. http://dx.doi.org/10.1109/icsmc.2009.5346035.

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Pont-Tuset, Jordi, and Ferran Marques. "Contour detection using Binary Partition Trees." In 2010 17th IEEE International Conference on Image Processing (ICIP 2010). IEEE, 2010. http://dx.doi.org/10.1109/icip.2010.5652339.

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Reports on the topic "Image partition"

1

Mitra, Suman K., C. A. Murthy, and Malay K. Kundu. A Technique for Image Magnification Using Partitioned Iterative Function System. Fort Belvoir, VA: Defense Technical Information Center, July 1999. http://dx.doi.org/10.21236/ada370871.

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Potamianos, Gerasimos, and John Goutsias. Stochastic Simulation Techniques for Partition Function Approximation of Gibbs Random Field Images. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada238611.

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