Academic literature on the topic 'DUPLICATE REGION DETECTION'
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Journal articles on the topic "DUPLICATE REGION DETECTION"
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Wang, Xiaofeng, Guanghui He, Chao Tang, Yali Han, and Shangping Wang. "Keypoints-Based Image Passive Forensics Method for Copy-Move Attacks." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 03 (February 22, 2016): 1655008. http://dx.doi.org/10.1142/s0218001416550089.
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A novel image passive forensics method for copy-move forgery detection is proposed. The proposed method combines block matching technology and feature point matching technology, and breaks away from the general framework of the visual feature-based approach that used local visual feature such as SIFT and followed by a clustering procedure to group feature points that are spatially close. In our work, image keypoints are extracted using Harris detector, and the statistical features of keypoint neighborhoods are used to generate forensics features. Then we proposed a new forensics features matching approach, in which, a region growth technology and a mismatch checking approach are developed to reduce mismatched keypoints and improve detected accuracy. We also develop a duplicate region detection method based on the distance frequency of corresponding keypoint pairs. The proposed method can detect duplicate regions for high resolution images. It has higher detection accuracy and computation efficiency. Experimental results show that the proposed method is robust for content-preserving manipulations such as JPEG compression, gamma adjustment, filtering, luminance enhancement, blurring, etc.
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Chen, Likai, Wei Lu, and Jiangqun Ni. "An Image Region Description Method Based on Step Sector Statistics and its Application in Image Copy-Rotate/Flip-Move Forgery Detection." International Journal of Digital Crime and Forensics 4, no. 1 (January 2012): 49–62. http://dx.doi.org/10.4018/jdcf.2012010104.
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A robust method for local image region feature description based on step sector statistics is proposed in this paper. The means and the standard deviations along the radial direction of the circle image region are extracted through the sector masks, and the rearrangement of these statistics makes this image region description method rotation-robust. The proposed description method is applied in the detection of copy-rotate-move forgery, and it can detect the exact rotation angle between the duplicate regions. With minor extension, the proposed description method can also be applied in the detection of copy-flip-move forgery. The experimental results show that the proposed description method can work well for the detection of copy-rotate/flip-move forgery.
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Pandey, Ramesh Chand, Sanjay Kumar Singh, and K. K. Shukla. "Passive Copy- Move Forgery Detection Using Speed-Up Robust Features, Histogram Oriented Gradients and Scale Invariant Feature Transform." International Journal of System Dynamics Applications 4, no. 3 (July 2015): 70–89. http://dx.doi.org/10.4018/ijsda.2015070104.
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Copy-Move is one of the most common technique for digital image tampering or forgery. Copy-Move in an image might be done to duplicate something or to hide an undesirable region. In some cases where these images are used for important purposes such as evidence in court of law, it is important to verify their authenticity. In this paper the authors propose a novel method to detect single region Copy-Move Forgery Detection (CMFD) using Speed-Up Robust Features (SURF), Histogram Oriented Gradient (HOG), Scale Invariant Features Transform (SIFT), and hybrid features such as SURF-HOG and SIFT-HOG. SIFT and SURF image features are immune to various transformations like rotation, scaling, translation, so SIFT and SURF image features help in detecting Copy-Move regions more accurately in compared to other image features. Further the authors have detected multiple regions COPY-MOVE forgery using SURF and SIFT image features. Experimental results demonstrate commendable performance of proposed methods.
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Li, Jianxiang, Yan Tian, Yiping Xu, and Zili Zhang. "Oriented Object Detection in Remote Sensing Images with Anchor-Free Oriented Region Proposal Network." Remote Sensing 14, no. 5 (March 3, 2022): 1246. http://dx.doi.org/10.3390/rs14051246.
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Oriented object detection is a fundamental and challenging task in remote sensing image analysis that has recently drawn much attention. Currently, mainstream oriented object detectors are based on densely placed predefined anchors. However, the high number of anchors aggravates the positive and negative sample imbalance problem, which may lead to duplicate detections or missed detections. To address the problem, this paper proposes a novel anchor-free two-stage oriented object detector. We propose the Anchor-Free Oriented Region Proposal Network (AFO-RPN) to generate high-quality oriented proposals without enormous predefined anchors. To deal with rotation problems, we also propose a new representation of an oriented box based on a polar coordinate system. To solve the severe appearance ambiguity problems faced by anchor-free methods, we use a Criss-Cross Attention Feature Pyramid Network (CCA-FPN) to exploit the contextual information of each pixel and its neighbors in order to enhance the feature representation. Extensive experiments on three public remote sensing benchmarks—DOTA, DIOR-R, and HRSC2016—demonstrate that our method can achieve very promising detection performance, with a mean average precision (mAP) of 80.68%, 67.15%, and 90.45%, respectively, on the benchmarks.
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Baxter, Nardia J., Julie Scanlan, Paolo De Marco, Ann P. Wood, and J. Colin Murrell. "Duplicate Copies of Genes Encoding Methanesulfonate Monooxygenase in Marinosulfonomonas methylotropha Strain TR3 and Detection of Methanesulfonate Utilizers in the Environment." Applied and Environmental Microbiology 68, no. 1 (January 2002): 289–96. http://dx.doi.org/10.1128/aem.68.1.289-296.2002.
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ABSTRACT Marinosulfonomonas methylotropha strain TR3 is a marine methylotroph that uses methanesulfonic acid (MSA) as a sole carbon and energy source. The genes from M. methylotropha strain TR3 encoding methanesulfonate monooxygenase, the enzyme responsible for the initial oxidation of MSA to formaldehyde and sulfite, were cloned and sequenced. They were located on two gene clusters on the chromosome of this bacterium. A 5.0-kbp HindIII fragment contained msmA, msmB, and msmC, encoding the large and small subunits of the hydroxylase component and the ferredoxin component, respectively, of the methanesulfonate monooxygenase, while a 6.5-kbp HindIII fragment contained duplicate copies of msmA and msmB, as well as msmD, encoding the reductase component of methanesulfonate. Both sets of msmA and msmB genes were virtually identical, and the derived msmA and msmB sequences of M. methylotropha strain TR3, compared with the corresponding hydroxylase from the terrestrial MSA utilizer Methylosulfonomonas methylovora strain M2 were found to be 82 and 69% identical. The msmA gene was investigated as a functional gene probe for detection of MSA-utilizing bacteria. PCR primers spanning a region of msmA which encoded a unique Rieske [2Fe-2S] binding region were designed. These primers were used to amplify the corresponding msmA genes from newly isolated Hyphomicrobium, Methylobacterium, and Pedomicrobium species that utilized MSA, from MSA enrichment cultures, and from DNA samples extracted directly from the environment. The high degree of identity of these msmA gene fragments, compared to msmA sequences from extant MSA utilizers, indicated the effectiveness of these PCR primers in molecular microbial ecology.
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Nguyen, Hoanh. "Improving Faster R-CNN Framework for Fast Vehicle Detection." Mathematical Problems in Engineering 2019 (November 22, 2019): 1–11. http://dx.doi.org/10.1155/2019/3808064.
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Vision-based vehicle detection plays an important role in intelligent transportation systems. With the fast development of deep convolutional neural networks (CNNs), vision-based vehicle detection approaches have achieved significant improvements compared to traditional approaches. However, due to large vehicle scale variation, heavy occlusion, or truncation of the vehicle in an image, recent deep CNN-based object detectors still showed a limited performance. This paper proposes an improved framework based on Faster R-CNN for fast vehicle detection. Firstly, MobileNet architecture is adopted to build the base convolution layer in Faster R-CNN. Then, NMS algorithm after the region proposal network in the original Faster R-CNN is replaced by the soft-NMS algorithm to solve the issue of duplicate proposals. Next, context-aware RoI pooling layer is adopted to adjust the proposals to the specified size without sacrificing important contextual information. Finally, the structure of depthwise separable convolution in MobileNet architecture is adopted to build the classifier at the final stage of the Faster R-CNN framework to classify proposals and adjust the bounding box for each of the detected vehicle. Experimental results on the KITTI vehicle dataset and LSVH dataset show that the proposed approach achieved better performance compared to original Faster R-CNN in both detection accuracy and inference time. More specific, the performance of the proposed method is improved comparing with the original Faster R-CNN framework by 4% on the KITTI test set and 24.5% on the LSVH test set.
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Clothier, Kristin A., Simone Stoute, Andrea Torain, and Beate Crossley. "Validation of a real-time PCR assay for high-throughput detection of Avibacterium paragallinarum in chicken respiratory sites." Journal of Veterinary Diagnostic Investigation 31, no. 5 (July 26, 2019): 714–18. http://dx.doi.org/10.1177/1040638719866484.
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Avibacterium paragallinarum is the causative agent of infectious coryza, a highly contagious respiratory disease in chickens. Given its fastidious nature, this bacterium is difficult to recover and identify, particularly from locations colonized by normal bacterial flora. Standard PCR methods have been utilized for detection but are labor-intensive and not feasible for high-throughput testing. We evaluated a real-time PCR (rtPCR) method targeting the HPG-2 region of A. paragallinarum, and validated a high-throughput extraction for this assay. Using single-tube extraction, the rtPCR detected 4 A. paragallinarum (ATCC 29545T and 3 clinical) isolates with a limit of detection (LOD) of 10 cfu/mL and a PCR efficiency of 89–111%. Cross-reaction was not detected with 33 non– A. paragallinarum, all close relatives from the family Pasteurellaceae. Real-time PCR testing on extracts of 66 clinical samples (choana, sinus, or trachea) yielded 98.2% (35 of 36 on positives, 30 of 30 on negatives) agreement with conventional PCR. Duplicate samples tested in a 96-well format extraction in parallel with the single-tube method produced equivalent LOD on all A. paragallinarum isolates, and 96.8% agreement on 93 additional clinical samples extracted with both procedures. This A. paragallinarum rtPCR can be utilized for outbreak investigations and routine monitoring of susceptible flocks.
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Asmann, Yan W., Vivekananda Sarangi, Bruce W. Eckloff, Julie M. Cunningham, Samantha J. McDonough, Yeon K. Lee, Eric D. Wieben, et al. "Comparison Of Single Nucleotide Mutations (SNVs) and Copy Number Variants (CNVs) Detection In Formalin Fixed Paraffin Embedded (FFPE) and Paired Frozen Tumor Tissues Using Target Capture and Sequencing Approach." Blood 122, no. 21 (November 15, 2013): 1784. http://dx.doi.org/10.1182/blood.v122.21.1784.1784.
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Abstract Background Next Generation sequencing (NGS) is a powerful tool to identify somatic mutations associated with tumor onset and drug response. While it is well suited for high quality fresh/frozen samples, NGS is not proven for FFPE tissue which is the most common type of clinical specimen. Since the nucleic acids can be readily extracted from FFPE samples for a variety of genomic analyses, a comparative mutational analysis of paired frozen and FFPE tissues is urgently needed. Our long term goal is to establish a lab protocol to detect mutations in FFPE tumors using a targeted capture and sequencing approach for genes of interest. This pilot study focuses on the comparison of FFPE and frozen samples to test the validity of using FFPE tissues in such application. Methods Gene Selection: 128 genes associated with known pathogenic mutations in lymphoma Sample Selection: 9 diffuse large B-cell lymphoma (DLBCL) cases with FFPE, frozen and germline samples, as well as 10 frozen normal lymphatic tissues as references for CNV detections Capture Probe Design: We targeted coding exons and UTR, as well as the evolutionarily conserved intronic regions. The capture probes were designed using the Agilent eArray tool. The titling density of the probes was set to 3 probes overlapping with every base in the target region to improve the capture efficiency in FFPE samples. The least stringent masking of the repeat regions was allowed to include regions with small repeats that are shorter than the length of the sequencing reads (100-bp). In addition, boosting parameters were picked to set various levels of probe replication in different regions in order to minimize the local coverage differences (e.g. between regions of different GC contents) Sequencing and Bioinformatics: The target capture and sequencing were performed by the Mayo Clinic Medical Genome Facility. The reads were mapped to Human Reference Genome Build 37 using Novalign, and SNVs were called using GATK. The CNVs were identified using an in-house developed algorithm, patternCNV. Results The designed probes covered 99.65937% of the target regions. We generated 2.2-6.7 Gbp of reads per sample, 57.4-71.5% of which were on target. This equalled an average coverage of 2100-6700 folds which is 10-30 times higher than the minimal coverage recommended by Agilent. Due to this high coverage, we observed duplicate reads that accounted for 7.7-73.5% of the total reads. When we analysed the data with and without the duplicated reads, the concordance of the called SNVs was between 84-93% out of 207-249 mutated positions per trio-sample. There were 7.8-8.9% and 1.1-2.2% unique SNVs per sample by excluding or including duplicate reads, respectively. The dis-concordances were mostly missed calls, where a SNV was observed in only 1 or 2 of the trio samples. The missed calls from frozen samples ranged from 0-10.4% compared to 1.4-10.4% from the FFPE tissues, with 0.88-2.4% more SNVs missed in FFPE. Further analyses showed that all of the missing calls came from the lack of or low coverage of the corresponding positions. There were also differences of the called SNVs between the trio samples. However, this was extremely rare. Only 2 out of the 9 trio samples at a total of 3 positions had disagreements in called SNVs between FFPE and frozen tissues, all due to the allelic imbalance where the percentage of reads supporting the alternative alleles were below 20%. Therefore, this dis-concordance can be removed by back-filling of the read-level information for each position. Unfortunately only 11.9-47.4% of the CNVs called in frozen tissues were identified in FFPE samples, due to the widely various coverage in FFPE samples. The consequent large noises of the log ratio values between the FFPEs and normal references significantly reduced the sensitivity for CNV calling. Conclusions This pilot study compared the performance of SNV and CNV detection in FFPE and paired frozen tissues using a target capture and sequencing approach. With a capture probe design strategized to benefit FFPE samples, we observed SNV detection rates in FFPE that were only slightly lower (0.88-2.4%) than those of frozen tissues due to poor coverage of some positions in FFPE samples. With a proper back-filling step, there was no dis-concordance of the called SNVs between FFPE and frozen samples. However, CNV detections in FFPE were more problematic due to the un-predictable regional coverage in FFPE samples. Disclosures: No relevant conflicts of interest to declare.
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Bande, Faruku, Siti Suri Arshad, Latiffah Hassan, and Zunita Zakaria. "Molecular Detection, Phylogenetic Analysis, and Identification of Transcription Motifs in Feline Leukemia Virus from Naturally Infected Cats in Malaysia." Veterinary Medicine International 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/760961.
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A nested PCR assay was used to determine the viral RNA and proviral DNA status of naturally infected cats. Selected samples that were FeLV-positive by PCR were subjected to sequencing, phylogenetic analysis, and motifs search. Of the 39 samples that were positive for FeLV p27 antigen, 87.2% (34/39) were confirmed positive with nested PCR. FeLV proviral DNA was detected in 38 (97.3%) of p27-antigen negative samples. Malaysian FeLV isolates are found to be highly similar with a homology of 91% to 100%. Phylogenetic analysis revealed that Malaysian FeLV isolates divided into two clusters, with a majority (86.2%) sharing similarity with FeLV-K01803 and fewer isolates (13.8%) with FeLV-GM1 strain. Different enhancer motifs including NF-GMa, Krox-20/WT1I-del2, BAF1, AP-2, TBP, TFIIF-beta, TRF, and TFIID are found to occur either in single, duplicate, triplicate, or sets of 5 in different positions within the U3-LTR-gag region. The present result confirms the occurrence of FeLV viral RNA and provirus DNA in naturally infected cats. Malaysian FeLV isolates are highly similar, and a majority of them are closely related to a UK isolate. This study provides the first molecular based information on FeLV in Malaysia. Additionally, different enhancer motifs likely associated with FeLV related pathogenesis have been identified.
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Zimina, V. N., O. E. Mikova, T. A. Varetskaya, D. A. Oborin, S. Yu Degtyareva, and V. I. Sergevnin. "The spectrum of primary drug resistance of Mycobacterium tuberculosis in patients with tuberculosis in relation to human immunodeficiency virus status." Terapevticheskii arkhiv 89, no. 11 (November 15, 2017): 50–54. http://dx.doi.org/10.17116/terarkh2017891150-54.
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Aim. To estimate the detection rate and spectrum of primary drug resistance of Mycobacterium tuberculosis (MBT) in patients with tuberculosis (TB) in relation to their human immunodeficiency virus (HIV) status in a region with high HIV infection rates (the Perm Territory) and to compare of drug-resistant MBT (DR-MBT) in patients with HIV/TB co-infection, by using phenotypic and molecular genetic testing (MGT) methods. Subjects and methods. The results of sputum bacteriological examination were analyzed in 178 HIV-infected patients and 354 non-HIV-infected individuals with a TB diagnosis made in the period July 1, 2014 to August 1, 2015. The diagnostic algorithm for all patients involved a duplicate sputum test for MBT by two techniques: fluorescence microscopy (FM) and inoculation into the Levenstein-Jensen dense culture medium. In patients with HIV/TB, the bacteriological examination was complemented with two more methods: detection of MBT DNA by a real-time polymerase chain reaction assay using the AmpliTube-RV system (Synthol, Russia); and inoculation into the Middlebrook liquid nutrient medium, by applying the automated BACTEC MGIT 960 system. Results. In patients with HIV/TB, the sensitivity of FM proved to be lower than in those with TB (24.2 and 32.8%, respectively; p0.05). The primary drug resistance of MBT in patients with HIV-TB was higher than that in HIV-negative individuals (60.2 and 41.6%, respectively; p
Dissertations / Theses on the topic "DUPLICATE REGION DETECTION"
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YADAV, PRASHIT. "DETECTION OF COPY MORE FORGERY IN DIGITAL IMAGES USING AN OPTIMIZED BLOCK BASED APPROACH." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/14922.
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Technology is growing exponentially and so does the sophistication of various imaging tools
that makes it easier for a person to forge digital images. There are several types of forgeries
which are done on images out of which Copy-Move is one of the most widely used. In this
type of forgery a portion of an image is copied and pasted over to another portion to conceal
some information. Several approaches have been developed so far to detect such kind of
forgery. In the block based approach the image is divided into overlapping blocks and each
block is matched against every other block for similarity. However such a matching would be
computationally expensive, thus each block’s dimensionality is reduced by extracting its vital
features and using this information for representation of the block. To extract the features we
first applied the Laplacian of Gaussian filter on the image to highlight the areas of interest
such as edges, blobs, etc. Subsequently we used Discrete Cosine Transform algorithm on
each block to generate DCT coefficient matrix for each block. The DCT coefficients matrix is
quantized and averaging is used to extract a feature set with reduce dimensionality. Now
these feature vectors with respect to each block are stored in a matrix called feature vector
matrix. The matrix is then lexicographically sorted so that vectors corresponding to similar
blocks come adjacent to each other. The decision of forgery can then be taken if a number of
connected/similar blocks are equidistant to each other. The feature extraction is vital as not
only does it reduce the computation complexity but choosing the correct set of features makes
an approach invariant to various image manipulations such as rotation, translation, scaling,etc.
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KUMAR, AKSHAT. "DETECTING DUPLICATE REGIONS IN DIGITAL IMAGES USING IMPROVED LOCALIZATION METHOD." Thesis, 2014. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15630.
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Now days, the uses of digital images has increased and so has the forgery mechanisms. Copy-Move forgery is one of the types of image forgery. In the case of copy-move forgery one small region of image is replaced with another region within the same image. Many algorithms already developed for detecting copy-move regions but the major problem for most of the algorithms are localization of duplicate regions within same image after detecting copy-move part. Here we present an efficient approach for detecting duplicate regions in a digital image. In our method, we have used PCA (Principal Component Analysis) to the input image for obtaining compressed image. For obtaining feature vector of each block, we divide the image into number of overlapping blocks. These feature vectors are calculated with the help of principal component analysis. Here we represent eigenvector as feature vector. Lexicographic sorting is henceforth applied to locate the similar feature vector of each block. If two or more feature vectors have same value then this indicates that image forgery has been done. But we cannot guarantee of image forgery because in some cases, feature vectors may be same in an image. Hence, we calculate total number of connected blocks with in the same distance. If the numbers of blocks are greater than a threshold value then image has been forged by duplicate regions, but if numbers of blocks are less than a threshold value then image has not been forged. After that, localization method is used for getting number of pixels that have been copied and pasted. With the help of our proposed method, duplicate regions in an image can be detected more accurately and with less computational complexity as compared to other methods.
Book chapters on the topic "DUPLICATE REGION DETECTION"
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Mahdian, Babak, and Stanislav Saic. "Detection of Near-Duplicated Image Regions." In Advances in Soft Computing, 187–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75175-5_24.
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Ardizzone, Edoardo, and Giuseppe Mazzola. "Detection of Duplicated Regions in Tampered Digital Images by Bit-Plane Analysis." In Image Analysis and Processing – ICIAP 2009, 893–901. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04146-4_95.
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Le-Tien, Thuong, Tan Huynh-Ngoc, Tu Huynh-Kha, and Luong Marie. "Zernike Moment-Based Approach for Detecting Duplicated Image Regions by a Modified Method to Reduce Geometrical and Numerical Errors." In Computational Science and Its Applications -- ICCSA 2015, 458–75. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21410-8_36.
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Zhao, Jie, Qiuzi Wang, Jichang Guo, Lin Gao, and Fusheng Yang. "An Overview on Passive Image Forensics Technology for Automatic Computer Forgery." In Cyber Warfare and Terrorism, 509–20. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2466-4.ch031.
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Currently, with the popularity of sophisticated image editing tools like Photoshop, it is becoming very difficult to discriminate between an authentic image and its manipulated version, which poses a serious social problem of debasing the credibility of photographic images as definite records of events. Passive image forgery detection technology, as one main branch of image forensics, has been regarded as the promising research interest due to its versatility and universality. Automatic computer forgery employs computer intelligent algorithms to forge an image in an automatic way, which is rather more complex than copy-move forgery since the source of duplicated region could be non-continuous. In this paper, the authors provide a comprehensive overview of the state-of-the-art passive detection methods for automatic computer forgery.
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Zhao, Jie, Qiuzi Wang, Jichang Guo, Lin Gao, and Fusheng Yang. "An Overview on Passive Image Forensics Technology for Automatic Computer Forgery." In Digital Forensics and Forensic Investigations, 27–38. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-3025-2.ch003.
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Currently, with the popularity of sophisticated image editing tools like Photoshop, it is becoming very difficult to discriminate between an authentic image and its manipulated version, which poses a serious social problem of debasing the credibility of photographic images as definite records of events. Passive image forgery detection technology, as one main branch of image forensics, has been regarded as the promising research interest due to its versatility and universality. Automatic computer forgery employs computer intelligent algorithms to forge an image in an automatic way, which is rather more complex than copy-move forgery since the source of duplicated region could be non-continuous. In this paper, the authors provide a comprehensive overview of the state-of-the-art passive detection methods for automatic computer forgery.
Conference papers on the topic "DUPLICATE REGION DETECTION"
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Jaberi, Maryam, George Bebis, Muhammad Hussain, and Ghulam Muhammad. "Improving the detection and localization of duplicated regions in copy-move image forgery." In 2013 18th International Conference on Digital Signal Processing (DSP). IEEE, 2013. http://dx.doi.org/10.1109/icdsp.2013.6622700.
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Li, Guohui, Qiong Wu, Dan Tu, and Shaojie Sun. "A Sorted Neighborhood Approach for Detecting Duplicated Regions in Image Forgeries Based on DWT and SVD." In Multimedia and Expo, 2007 IEEE International Conference on. IEEE, 2007. http://dx.doi.org/10.1109/icme.2007.4285009.
Full textReports on the topic "DUPLICATE REGION DETECTION"
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Bercovier, Herve, and Ronald P. Hedrick. Diagnostic, eco-epidemiology and control of KHV, a new viral pathogen of koi and common carp. United States Department of Agriculture, December 2007. http://dx.doi.org/10.32747/2007.7695593.bard.
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Original objectives and revisions-The proposed research included these original objectives: field validation of diagnostic tests (PCR), the development and evaluation of new sensitive tools (LC-PCR/TaqManPCR, antibody detection by ELISA) including their use to study the ecology and the epidemiology of KHV (virus distribution in the environment and native cyprinids) and the carrier status of fish exposed experimentally or naturally to KHV (sites of virus replication and potential persistence or latency). In the course of the study we completed the genome sequence of KHV and developed a DNA array to study the expression of KHV genes in different conditions. Background to the topics-Mass mortality of koi or common carp has been observed in Israel, USA, Europe and Asia. These outbreaks have reduced exports of koi from Israel and have created fear about production, import, and movements of koi and have raised concerns about potential impacts on native cyprinid populations in the U.S.A. Major conclusions-A suite of new diagnostic tools was developed that included 3 PCR assays for detection of KHV DNA in cell culture and fish tissues and an ELISA assay capable of detecting anti-KHV antibodies in the serum of koi and common carp. The TKPCR assay developed during the grant has become an internationally accepted gold standard for detection of viral DNA. Additionally, the ELISA developed for detecting serum anti-KHV antibodies is now in wide use as a major nonlethal screening tool for evaluating virus status of koi and common carp populations. Real time PCR assays have been able to detect viral DNA in the internal organs of survivors of natural and wild type vaccine exposures at 1 and 10³ genome equivalents at 7 months after exposure. In addition, vaccinated fish were able to transmit the virus to naive fish. Potential control utilizing hybrids of goldfish and common carp for production demonstrated they were considerably more resistant than pure common carp or koi to both KHV (CyHV-3). There was no evidence that goldfish or other tested endemic cyprinids species were susceptible to KHV. The complete genomic sequencing of 3 strains from Japan, the USA, and Israel revealed a 295 kbp genome containing a 22 kbp terminal direct repeat encoding clear gene homologs to other fish herpesviruses in the family Herpesviridae. The genome encodes156 unique protein-coding genes, eight of which are duplicated in the terminal repeat. Four to seven genes are fragmented and the loss of these genes may be associated with the high virulence of the virus. Viral gene expression was studies by a newly developed chip which has allowed verification of transcription of most all hypothetical genes (ORFs) as well as their kinetics. Implications, both scientific and agricultural- The results from this study have immediate application for the control and management of KHV. The proposal provides elements key to disease management with improved diagnostic tools. Studies on the ecology of the virus also provide insights into management of the virus at the farms that farmers will be able to apply immediately to reduce risks of infections. Lastly, critical issues that surround present procedures used to create “resistant fish” must be be resolved (e.g. carriers, risks, etc.). Currently stamping out may be effective in eradicating the disease. The emerging disease caused by KHV continues to spread. With the economic importance of koi and carp and the vast international movements of koi for the hobby, this disease has the potential for even further spread. The results from our studies form a critical component of a comprehensive program to curtail this emerging pathogen at the local, regional and international levels.