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Academic literature on the topic 'Zernike moments'

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Published: 4 June 2021
Last updated: 11 September 2023

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Journal articles on the topic "Zernike moments"

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Chong, Chee-Way, P. Raveendran, and R. Mukundan. "An Efficient Algorithm for Fast Computation of Pseudo-Zernike Moments." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 06 (September 2003): 1011–23. http://dx.doi.org/10.1142/s0218001403002769.

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Pseudo-Zernike moments have better feature representation capability, and are more robust to image noise than those of the conventional Zernike moments. However, due to the computation complexity of pseudo-Zernike polynomials, pseudo-Zernike moments are yet to be extensively used as feature descriptors as compared to Zernike moments. In this paper, we propose two new algorithms, namely coefficient method and p-recursive method, to accelerate the computation of pseudo-Zernike moments. Coefficient method calculates polynomial coefficients recursively. It eliminates the need of using factorial functions. Individual order or index of pseudo-Zernike moments can be derived independently, which is useful if selected orders or indices of moments are needed as pattern features. p-recursive method uses a combination of lower order polynomials to derive higher order polynomials with the same index q. Fast computation is achieved because it eliminates the requirements of calculating polynomial coefficients, Bpqk, and power of radius, rk, in each polynomial. The performance of the proposed algorithms on moment computation and image reconstruction, as compared to those of the present methods, are experimentally verified using a set of binary and grayscale images.
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Al-Rawi, Mohammed. "Fast Zernike moments." Journal of Real-Time Image Processing 3, no. 1-2 (January 8, 2008): 89–96. http://dx.doi.org/10.1007/s11554-007-0069-2.

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Indian, Ajay, and Karamjit Bhatia. "An Approach to Recognize Handwritten Hindi Characters Using Substantial Zernike Moments With Genetic Algorithm." International Journal of Computer Vision and Image Processing 11, no. 2 (April 2021): 66–81. http://dx.doi.org/10.4018/ijcvip.2021040105.

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A technique to recognize off-line handwritten Hindi character is suggested by employing Zernike complex moments like a tool to describe the characteristics of a character. Further, an algorithm for selecting the features is employed to identify the substantial image moments from the extracted moments, as the extracted moments may have some insignificant ones. Insignificant moments can increase the computational time and can also degrade the classification accuracy. Thus, the objectives of the study are twofold: (1) to find the important Zernike moments by employing the Genetic algorithm (GA) and (2) the classification of each character is performed using neural network. This way, the performance of the proposed technique is evaluated on two parameters (i.e., speed and recognition accuracy). Further, the efficacy of GA for selecting the moment features is assessed, and the efficacy of selected Zernike complex moments using GA is analyzed for handwritten Hindi characters. Here, the authors used a resilient backpropagation learning algorithm (RPROP) as a classification model.
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Theodoridis, Thomas, Kostas Loumponias, Nicholas Vretos, and Petros Daras. "Zernike Pooling: Generalizing Average Pooling Using Zernike Moments." IEEE Access 9 (2021): 121128–36. http://dx.doi.org/10.1109/access.2021.3108630.

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Qin, Hua Feng, Lan Qin, and Jun Liu. "A Novel Recurrence Method for the Fast Computation of Zernike Moments." Applied Mechanics and Materials 121-126 (October 2011): 1868–72. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.1868.

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A new method is proposed for fast computation of Zernike moments. This method presents a recursive relation to compute the entire set of Zernike moments. The fast computation is achieved because it involves less addition and multiplication operations. The experimental results show that the proposed method for the fast computation of Zernike moments is much more efficient than existing fast methods in most cases
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Deng, An-Wen, and Chih-Ying Gwo. "Parallel Computing Zernike Moments via Combined Algorithms." SIJ Transactions on Computer Science Engineering & its Applications (CSEA) 04, no. 03 (June 28, 2016): 01–09. http://dx.doi.org/10.9756/sijcsea/v4i3/04020050101.

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Liu, Zhenghui, and Hongxia Wang. "A Speech Content Authentication Algorithm Based on Pseudo-Zernike Moments in DCT Domain." International Journal of Digital Crime and Forensics 5, no. 3 (July 2013): 15–34. http://dx.doi.org/10.4018/jdcf.2013070102.

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A speech content authentication algorithm based on pseudo-Zernike moments in DCT domain is proposed in this paper, which is aimed at some shortcomings in some existing digital watermark schemes. The definition of coefficients self-correlation degree is given. Then the frequency domain watermark embedding method based on pseudo-Zernike moments in DCT domain is proposed. Watermark bits are generated by coefficients self-correlation degree and embedded by quantizing the pseudo-Zernike moments of DCT domain low-frequency coefficients. Comparing with the existing audio watermark algorithms based on pseudo-Zernike moments, the algorithm increases the watermarking embedding capacity and improves the efficiency greatly. Theoretical analysis and experimental evaluation results show that the proposed speech content authentication algorithm is effective.
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Singh, Chandan, Ekta Walia, and Neerja Mittal. "Discriminative Zernike and Pseudo Zernike Moments for Face Recognition." International Journal of Computer Vision and Image Processing 2, no. 2 (April 2012): 12–35. http://dx.doi.org/10.4018/ijcvip.2012040102.

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Usually magnitude coefficients of some selected orders of ZMs and PZMs have been used as invariant image features. The careful selection of the set of features, with higher discrimination competence, may increase the recognition performance. In this paper, the authors have used a statistical method to estimate the discrimination strength of all the extracted coefficients of ZMs and PZMs whereas for classification, only the coefficients with estimated higher discrimination strength are used in the feature vector. The performance of these selected Discriminative ZMs (DZMs) and Discriminative PZMs (DPZMs) features have been compared to that of their corresponding conventional approaches on YALE, ORL and FERET databases against illumination, expression, scale and pose variations. An extension to these DZMs and DPZMs have been proposed by combining them with PCA and FLD. It has been observed from the exhaustive experimentation that the recognition rate is improved by 2-6%, at reduced dimensions and with less computational complexity, than that of using the successive ZMs and PZMs features.
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Gao, Wenhan, Shanmin Zhou, Shuo Liu, Tao Wang, Bingbing Zhang, Tian Xia, Yong Cai, and Jianxing Leng. "Research on an Underwater Target-Tracking Method Based on Zernike Moment Feature Matching." Journal of Marine Science and Engineering 11, no. 8 (August 14, 2023): 1594. http://dx.doi.org/10.3390/jmse11081594.

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Sonar images have the characteristics of lower resolution and blurrier edges compared to optical images, which make the feature-matching method in underwater target tracking less robust. To solve this problem, we propose a particle filter (PF)-based underwater target-tracking method utilizing Zernike moment feature matching. Zernike moments are used to construct the feature-description vector for feature matching and contribute to the update of particle weights. In addition, the particle state transition method is optimized by using a first-order autoregressive model. In this paper, we compare Hu moments and Zernike moments, and we also compare whether to optimize the particle state transition on the tracking results or not based on the effects of each option. The experimental results based on the AUV (autonomous underwater vehicle) prove that the robustness and accuracy of this innovative method is better than the other combined methods mentioned in this paper.
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BADRA, FADY, ALA QUMSIEH, and GREGORY DUDEK. "ROBUST MOSAICING USING ZERNIKE MOMENTS." International Journal of Pattern Recognition and Artificial Intelligence 13, no. 05 (August 1999): 685–704. http://dx.doi.org/10.1142/s0218001499000409.

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This paper presents an approach to the registration of individual images to one another to produce a larger composite mosaic. The approach is based on the use of the moments of Zernike orthogonal polynomials to compute the relative scale, rotation and translation between the images. A preliminary stage involves the use of an attention-like operation to estimate potential approximate correspondence points between the images based on extrema of local edge element density. Experimental results illustrate that the technique is effective in a range of environments and over a broad range of image registration parameters. In particular, our method makes few assumptions regarding the image content and yet, unlike several alternative approaches, can perform registration for images with only a limited amount of overlap.
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Dissertations / Theses on the topic "Zernike moments"

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Khatchadourian, Sonia. "Mise en œuvre d'une architecture de reconnaissance de formes pourla détection de particules à partir d'images atmosphériques." Cergy-Pontoise, 2010. http://www.theses.fr/2010CERG0438.

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L'expérience HESS consiste en un système de télescopes permettant d'observer les rayonnements cosmiques. Compte tenu des résultats majeurs obtenus depuis son installation, la seconde phase du projet a été engagée. Celle-ci passe par l'ajout d'un télescope plus sensible et plus grand que ses prédécesseurs. Toutes les données collectées par ce télescope ne pouvant être conservées à cause des limites de stockage, un système de déclencheur (trigger) performant doit être mis en place. L'objectif de cette thèse est de proposer une solution de reconnaissance de formes en temps réel, embarquée sur le télescope. La première partie de la thèse a consisté à élaborer une chaine de reconnaissance des formes pour ce trigger. Une chaine de traitement à base de réseau de neurones et des moments de Zernike a été validée. La seconde partie de la thèse a porté sur l'implantation des algorithmes retenus sur FPGA en tenant compte des contraintes en termes de ressources et de temps d'exécution
The HESS experiment consists of a system of telescopes destined to observe cosmic rays. Since the project has achieved a high level of performances, a second phase of the project has been initiated. This implies the addition of a new telescope which is capable of collecting a huge amount of images. As all data collected by the telescope can not be retained because of storage limitations, a new real-time system trigger must be designed in order to select interesting events on the fly. The purpose of this thesis was to propose a trigger solution to efficiently discriminate events captured by the telescope. The first part of this thesis was to develop pattern recognition algorithms to be implemented within the trigger. A processing chain based on neural networks and Zernike moments has been validated. The second part of the thesis has focused on the implementation of the proposed algorithms onto FPGA, taking into account the application constraints in terms of resources and execution time
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Maalouf, Elie. "Contribution to fluorescence microscopy, 3D thick samples deconvolution and depth-variant PSF." Phd thesis, Université de Haute Alsace - Mulhouse, 2010. http://tel.archives-ouvertes.fr/tel-00594247.

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The 3-D fluorescence microscope has become the method of choice in biological sciences for living cells study. However, the data acquired with conventional3-D fluorescence microscopy are not quantitatively significant because of distortions induced by the optical acquisition process. Reliable measurements need the correction of theses distortions. Knowing the instrument impulse response, also known as the PSF, one can consider the backward process of convolution induced by the microscope, known as "deconvolution". However, when the system response is not invariant in the observation field, the classical algorithms can introduce large errors in the results. In this thesis we propose a new approach, which can be easily adapted to any classical deconvolution algorithm, direct or iterative, for bypassing the non-invariance PSF problem, without any modification to the later. Based on the hypothesis that the minimal error in a restored image using non-invariance assumption is located near the used PSF position, the EMMA (Evolutive Merging Masks Algorithm) blends multiple deconvolutions in the invariance assumption using a specific merging mask set. In order to obtain sufficient number of measured PSF at various depths for a better restoration using EMMA (or any other depth-variant deconvolution algorithm) we propose a 3D PSF interpolation algorithm based on the image moments theory using Zernike polynomials as decomposition base. The known PSF are decomposed into Zernike moments set and each moment's variation is fitted into a polynomial function, the resulting functions are then used to interpolate the needed PSF's Zernike moments set to reconstruct the interpolated PSF.
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Yau, Wai Chee, and waichee@ieee org. "Video Analysis of Mouth Movement Using Motion Templates for Computer-based Lip-Reading." RMIT University. Electrical and Computer Engineering, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20081209.162504.

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This thesis presents a novel lip-reading approach to classifying utterances from video data, without evaluating voice signals. This work addresses two important issues which are • the efficient representation of mouth movement for visual speech recognition • the temporal segmentation of utterances from video. The first part of the thesis describes a robust movement-based technique used to identify mouth movement patterns while uttering phonemes. This method temporally integrates the video data of each phoneme into a 2-D grayscale image named as a motion template (MT). This is a view-based approach that implicitly encodes the temporal component of an image sequence into a scalar-valued MT. The data size was reduced by extracting image descriptors such as Zernike moments (ZM) and discrete cosine transform (DCT) coefficients from MT. Support vector machine (SVM) and hidden Markov model (HMM) were used to classify the feature descriptors. A video speech corpus of 2800 utterances was collected for evaluating the efficacy of MT for lip-reading. The experimental results demonstrate the promising performance of MT in mouth movement representation. The advantages and limitations of MT for visual speech recognition were identified and validated through experiments. A comparison between ZM and DCT features indicates that th e accuracy of classification for both methods is very comparable when there is no relative motion between the camera and the mouth. Nevertheless, ZM is resilient to rotation of the camera and continues to give good results despite rotation but DCT is sensitive to rotation. DCT features are demonstrated to have better tolerance to image noise than ZM. The results also demonstrate a slight improvement of 5% using SVM as compared to HMM. The second part of this thesis describes a video-based, temporal segmentation framework to detect key frames corresponding to the start and stop of utterances from an image sequence, without using the acoustic signals. This segmentation technique integrates mouth movement and appearance information. The efficacy of this technique was tested through experimental evaluation and satisfactory performance was achieved. This segmentation method has been demonstrated to perform efficiently for utterances separated with short pauses. Potential applications for lip-reading technologies include human computer interface (HCI) for mobility-impaired users, defense applications that require voice-less communication, lip-reading mobile phones, in-vehicle systems, and improvement of speech-based computer control in noisy environments.
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Bigorgne, Erwan. "Détection et caractérisation de points singuliers pour l' appariement et l' indexation d' images couleurs." Paris 6, 2005. http://www.theses.fr/2005PA066270.

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Imada, Renata Nagima [UNESP]. "Reconhecimento de contorno de edifício em imagens de alta resolução usando os momentos complexos de Zernike." Universidade Estadual Paulista (UNESP), 2014. http://hdl.handle.net/11449/122215.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Nesta pesquisa foi estudado um m etodo de reconhecimento de contornos de telhado de edif cios em imagens digitais de alta resolu c~ao, que classi ca-os com rela c~ao a sua forma. O m etodo baseia-se nos momentos de Zernike, que s~ao baseados nos polin omios ortogonais de Zernike, em que cria-se um vetor de caracter sticas para cada regi~ao da imagem, que deve ser previamente segmentada de maneira que seus objetos sejam divididos em diferentes regi~oes. Este m etodo para a descri c~ao de forma baseia-se na area do objeto de interesse e possui a caracter stica dos momentos serem invariantes em rela c~ao as transforma c~oes geom etricas de rota c~ao, transla c~ao e escala, que o torna atrativo para o problema de an alise de imagem proposto. Desse modo, foi criada uma base de dados contendo esbo cos (ou modelos) de poss veis apari c~oes de contornos de telhado de edif cio numa dada cena, para que seja associado tamb em um vetor de caracter sticas de Zernike para estes esbo cos. Assim, a dist ancia euclidiana entre este vetor e o vetor de caracter sticas calculado a partir de uma regi~ao segmentada na imagem, permite dizer se a regi~ao dada corresponde a um contorno de edif cio ou a outro objeto. A capacidade de discrimina c~ao do m etodo proposto entre diferentes formas de edif cios, e tamb em entre formas de edif cios e n~ao edif cios foi avaliada experimentalmente e mostrou resultados positivos.
In this research, a method of recognition of building roof contours in high-resolution digital images which classi es them with respect to their form was studied. The method is based on Zernike moments, which are based on orthogonal Zernike polynomials and it creates a feature vector for each image region. The image segmentation has to be made rst to de ne di erent regions for its objects. This method for shape analysis is based on the object area of interest and the moments has the characteristic of being invariant under geometric transformations of rotation, translation and scaling, this makes it attractive to the proposed image analysis problem. Thus, a database containing sketches (or models) of possible appearances of building roof contours in a given scene was created, so a Zernike feature vector was also associated for these sketches. Therefore, the Euclidean distance between this vector and the feature vector calculated from a segmented region in the image lets say if the given region corresponds to a building contour or other object. The capacity of the proposed method in discriminating di erent building shapes and also in discriminating building shapes from non-building shapes was evaluated experimentally and it showed positive results.
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Imada, Renata Nagima. "Reconhecimento de contorno de edifício em imagens de alta resolução usando os momentos complexos de Zernike /." Presidente Prudente, 2014. http://hdl.handle.net/11449/122215.

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Orientador: Aluir Porfírio Dal Poz
Banca: Edson Aparecido Mitishita
Banca: Aylton Pagamisse
Resumo: Nesta pesquisa foi estudado um m etodo de reconhecimento de contornos de telhado de edif cios em imagens digitais de alta resolu c~ao, que classi ca-os com rela c~ao a sua forma. O m etodo baseia-se nos momentos de Zernike, que s~ao baseados nos polin^omios ortogonais de Zernike, em que cria-se um vetor de caracter sticas para cada regi~ao da imagem, que deve ser previamente segmentada de maneira que seus objetos sejam divididos em diferentes regi~oes. Este m etodo para a descri c~ao de forma baseia-se na area do objeto de interesse e possui a caracter stica dos momentos serem invariantes em rela c~ao as transforma c~oes geom etricas de rota c~ao, transla c~ao e escala, que o torna atrativo para o problema de an alise de imagem proposto. Desse modo, foi criada uma base de dados contendo esbo cos (ou modelos) de poss veis apari c~oes de contornos de telhado de edif cio numa dada cena, para que seja associado tamb em um vetor de caracter sticas de Zernike para estes esbo cos. Assim, a dist^ancia euclidiana entre este vetor e o vetor de caracter sticas calculado a partir de uma regi~ao segmentada na imagem, permite dizer se a regi~ao dada corresponde a um contorno de edif cio ou a outro objeto. A capacidade de discrimina c~ao do m etodo proposto entre diferentes formas de edif cios, e tamb em entre formas de edif cios e n~ao edif cios foi avaliada experimentalmente e mostrou resultados positivos.
Abstract: In this research, a method of recognition of building roof contours in high-resolution digital images which classi es them with respect to their form was studied. The method is based on Zernike moments, which are based on orthogonal Zernike polynomials and it creates a feature vector for each image region. The image segmentation has to be made rst to de ne di erent regions for its objects. This method for shape analysis is based on the object area of interest and the moments has the characteristic of being invariant under geometric transformations of rotation, translation and scaling, this makes it attractive to the proposed image analysis problem. Thus, a database containing sketches (or models) of possible appearances of building roof contours in a given scene was created, so a Zernike feature vector was also associated for these sketches. Therefore, the Euclidean distance between this vector and the feature vector calculated from a segmented region in the image lets say if the given region corresponds to a building contour or other object. The capacity of the proposed method in discriminating di erent building shapes and also in discriminating building shapes from non-building shapes was evaluated experimentally and it showed positive results.
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Bastos, Igor Leonardo Oliveira. "Reconhecimento de sinais da libras utilizando descritores de forma e redes neurais artificiais." Instituto de Matemática. Departamento de Ciência da Computação, 2015. http://repositorio.ufba.br/ri/handle/ri/19374.

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Gestos são ações corporais não-verbais voltadas para a expressão de algum significado. Estes incluem movimentos de mãos, face, braços, dedos, entre outros, sendo abordados por trabalhos que visam reconhecê-los para promover interações humanas com sistemas computacionais. Devido à grande aplicabilidade do reconhecimento de gestos, tem-se notado que estes trabalhos estão se tornando mais comuns, utilizando técnicas e metodologias mais elaboradas e capazes de prover resultados cada vez melhores. A opção por quais técnicas aplicar para o reconhecimento de gestos varia de acordo com a estratégia empregada em cada trabalho e quais aspectos são utilizados para este reconhecimento. Tem-se, por exemplo, trabalhos baseados no uso de modelos estatísticos. Outros optam pela aquisição de características geométricas de mãos e partes do corpo, enquanto outros, dentre os quais se enquadra o presente trabalho, optam pelo uso de descritores e classificadores, responsáveis por extrair características das imagens relevantes para o seu reconhecimento e; por realizar a classificação efetiva dos gestos baseado nestas informações. Neste âmbito, o presente trabalho visa elaborar, aplicar e apresentar uma abordagem para o reconhecimento de gestos, embasando-se em uma revisão da literatura a respeito das principais técnicas e metodologias empregadas para este fim e escolhendo como campo prático, a Língua Brasileira de Sinais (Libras). Para a extração de informações das imagens, optou-se pelo uso de um vetor de características resultante da aplicação dos descritores Histograma de Gradientes Orientados (HOG) e Momentos Invariantes de Zernike (MIZ), os quais voltam-se para as formas e contornos presentes nas imagens. Para o reconhecimento, foi utilizado o classificador Perceptron Multicamada, sendo este disposto em uma arquitetura onde o processo de classificação é dividido em 2 estágios. Devido à inexistência de datasets públicos da Libras, fez-se necessária, com o auxílio de especialistas da língua e alunos surdos, a criação de um dataset de 9600 imagens, as quais referem-se a 40 sinais da Libras. Isso fez com que a presente abordagem partisse desta criação do dataset até a etapa final de classificação dos sinais. Por fim, testes foram realizados e obteve-se 96,77% de taxa de acerto, evidenciando um alto índice de acerto. Este resultado foi validado considerando possíveis ameaças à abordagem, como a realização de testes considerando um indivíduo não-presente no conjunto de treinamento do classificador e a aplicação da abordagem em um dataset público de gestos.
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Khatchadourian, Sonia. "Mise en oeuvre d'une architecture de reconnaissance de formes pour la détection de particules à partir d'images atmosphériques." Phd thesis, Université de Cergy Pontoise, 2010. http://tel.archives-ouvertes.fr/tel-00783077.

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L'expérience HESS consiste en un système de télescopes permettant d'observer les rayonnements cosmiques. Compte tenu des résultats majeurs obtenus depuis son installation, la seconde phase du projet a été engagée. Celle-ci est en cours de réalisation et passe par l'ajout d'un télescope plus sensible et plus grand que ses prédécesseurs. Toutes les données collectées par ce télescope ne peuvent pas être conservées à cause des limites de stockage. Par conséquent, un système de déclencheur, dit trigger, performant doit être mis en place. L'objectif de cette thèse est de proposer une solution de reconnaissance de formes en temps réel dans un contexte fortement contraint et qui sera embarquée sur le télescope. La première partie de la thèse a consisté à élaborer une chaîne de reconnaissance des formes pour ce trigger. Une chaîne de traitement à base de réseau de neurones et des moments de Zernike a été validée. La seconde partie de la thèse a porté sur l'implantation des algorithmes retenus sur une cible FPGA en tenant compte des contraintes en termes de ressources et de temps d'exécution.
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Lieh-Cherng, Lin, and 林烈誠. "Zernike moments for 2D Shape Recognition." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/88401306062221330785.

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Lin, You-Tsai, and 林猷財. "Image Rotation Angle Estimation Using Rotation Invariant Features of Zernike Moments." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/10622265211779462331.

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碩士
國立交通大學
電機與控制工程系
89
An estimation approach of image rotation angle is proposed here. A basic assumption that the center of image rotation must be known is made, so that we can estimate the precise image rotation angles from the comparison between the rotated images and the reference one. Furthermore, the Zernike moment algorithm with subsampling and interpolation techniques can increase the image resolution and compute Zernike moments more accurately on the premise that keep the image acquiring hardware instrument unchanged. In addition, a K-means clustering algorithm is used to classify valuable entries from all the rotation angle candidates extracted via Zernike moments and sum up them by weighting factors based on image reconstruction. After that, the estimation of image rotation angle with high resolution is derived. Two experiments are reported which are on rotated images generated by computer and captured by CCD camera, respectively. The experimental results show that the proposed method has good performance for image rotation angle estimation.
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Book chapters on the topic "Zernike moments"

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Xin, Yongqing, Miroslaw Pawlak, and Simon Liao. "Image Reconstruction with Polar Zernike Moments." In Pattern Recognition and Image Analysis, 394–403. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11552499_45.

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Cura, Ezequiel, Mariano Tepper, and Marta Mejail. "Content-Based Emblem Retrieval Using Zernike Moments." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 79–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16687-7_15.

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Abdallah, Samer M., Eduardo M. Nebot, and David C. Rye. "Object recognition and orientation via Zernike moments." In Computer Vision — ACCV'98, 386–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63930-6_145.

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Chen, Shiyi, Yi Chen, Yanli Chen, Limengnan Zhou, and Hanzhou Wu. "Robust Video Watermarking Using Normalized Zernike Moments." In Lecture Notes in Computer Science, 323–36. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06791-4_26.

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Górniak, Aneta, and Ewa Skubalska-Rafajłowicz. "Object Classification Using Sequences of Zernike Moments." In Computer Information Systems and Industrial Management, 99–109. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59105-6_9.

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Bastos, Igor L. O., Larissa Rocha Soares, and William Robson Schwartz. "Pyramidal Zernike Over Time: A Spatiotemporal Feature Descriptor Based on Zernike Moments." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 77–85. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75193-1_10.

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Choksuriwong, A., H. Laurent, C. Rosenberger, and C. Maaoui. "Object Recognition Using Local Characterisation and Zernike Moments." In Advanced Concepts for Intelligent Vision Systems, 108–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11558484_14.

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Wang, Xiangyang, Tianxiao Ma, and Panpan Niu. "Digital Audio Watermarking Technique Using Pseudo-Zernike Moments." In Information and Communications Security, 459–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-11145-7_36.

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Biswas, Rajarshi, and Sambhunath Biswas. "Discrete Circular Mapping for Computation of Zernike Moments." In Lecture Notes in Computer Science, 86–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21786-9_16.

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Esther Rani, P., and R. Shanmuga Lakshmi. "Palmprint Recognition System Using Zernike Moments Feature Extraction." In Information and Communication Technologies, 449–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15766-0_72.

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Conference papers on the topic "Zernike moments"

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Sheng, Yulong. "Orthogonal invariant Fourier-Mellin moments." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.thl1.

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Conventional image moment invariants suffer from information redundancy and are sensitive to noise. We propose new orthogonal image moments based on the function set {Q n (r)exp(jmθ)}, where (r,θ) are polar coordinates and the polynomial Q n (r) is obtained by orthogonalizing the powers {r0,r1,r2,…, r n }. The moments are rotation invariant because of the circular Fourier expansion. The scale invariance is obtained by normalizing separately the power terms r n . This behavior is similar to that of the Zernike moments, but the Zernike circle polynomials are obtained by orthogonalizing the powers {r |m |,r |m |+2,r |m |+4,…}. The new moments are based on the separable circular-Fourier and radial-Mellin transform with the power n of the r n completely independent on the m. That allows much lower order n than that used in the Zernike moment and the pseudo-Zernike moments. Thus, the new moments would be less sensitive to noise. The orthogonal Fourier-Mellin moments may be expressed and calculated in terms of the complex moments. Only the definition of the complex moments should be modified to allow real valued moment orders.
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Yun Guo, Chunping Liu, and Shengrong Gong. "Improved algorithm for Zernike moments." In 2015 International Conference on Control, Automation and Information Sciences (ICCAIS). IEEE, 2015. http://dx.doi.org/10.1109/iccais.2015.7338682.

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Shen, Lixin, and Yunlong Sheng. "Distortion invariant pattern recognition using the orthogonal Fourier–Mellin moments." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.ws2.

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Scale and rotation by invariant pattern recognition is achieved using the orthogonal Fourier–Mellin moments, Q n (r)exp(jmθ), where Q n (r) are the polynomials on r and are generated by orthogonalizing the set of powers {r0,r1,…, r n }. The Q n (r) are in fact the modified Zernike radial polynomials without the restrictions that the radial moment orders must be even and greater than the circular moment orders |m|. The orthogonal Fourier–Mellin moments may be also calculated in the Cartesian coordinate system as the modified complex moments without the restriction that the moments order p and q must be positive integers. The Zernike moments have been shown to have the best overall performance among the various image moments. The performance of the new moments for pattern recognition is compared with that of the Zernike moments in terms of image representation, class separability, and noise sensitivity as functions of the number of the total moment features and of the radial orders of the moments. Experimental results show that for a given class of objects the orthogonal Fourier–Mellin moments use features of much lower radial orders for image classification, so it is then less sensitive to noise.
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Li Bo. "Accurate computation of Pseudo-Zernike moments." In 2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2015. http://dx.doi.org/10.1109/iccwamtip.2015.7493979.

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Ozbulak, Gokhan, and Muhittin Gokmen. "Corner detection by Local Zernike Moments." In 2015 23th Signal Processing and Communications Applications Conference (SIU). IEEE, 2015. http://dx.doi.org/10.1109/siu.2015.7130092.

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Jang, Han-Ul, Dai-Kyung Hyun, Dae-Jin Jung, and Heung-Kyu Lee. "Fingerprint-PKI authentication using Zernike moments." In 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014. http://dx.doi.org/10.1109/icip.2014.7026017.

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Papakostas, G. A., Y. S. Boutalis, D. A. Karras, and B. G. Mertzios. "Highly Compressed Zernike Moments by Smoothing." In 2007 14th International Workshop on Systems, Signals and Image Processing and 6th EURASIP Conference focused on Speech and Image Processing, Multimedia Communications and Services. IEEE, 2007. http://dx.doi.org/10.1109/iwssip.2007.4381188.

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Toxqui-Quitl, C., E. Velázquez-Ramírez, A. Padilla-Vivanco, J. Solís-Villarreal, and C. Santiago-Tepantlán. "Multifocus image fusion using Zernike moments." In SPIE Optical Engineering + Applications, edited by Andrew G. Tescher. SPIE, 2012. http://dx.doi.org/10.1117/12.930329.

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Gui, Jiangsheng, and Weida Zhou. "Fruit shape classification using Zernike moments." In International Conference on Image Processing and Pattern Recognition in Industrial Engineering, edited by Zhengyu Du and Bin Liu. SPIE, 2010. http://dx.doi.org/10.1117/12.866405.

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Liu, Hongmei, Wei Rui, and Jiwu Huang. "Binary Image Authentication using Zernike Moments." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4378972.

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