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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Tamililakkiya, V. Vani, K. Anna Univ Coll Engn Madras 600025 Tamil Nadu India

ISBN: (纸本)9783642240546

Automatic feature identification from orbital imagery would be of wide use in planetary science. For geo scientific applications, automatic shape-based feature detection offers a fast and non-subjective means of identifying geological structures within data. Most previously published examples of circular feature detection for geo scientific applications aimed to identify impact craters from optical or topographic data. Various techniques used include the texture analysis, template matching, and machine learning. In this paper, we propose a new method for the extraction of features from the planetary surface, based on the combination of several image processing techniques, including a shadow removal, watershed segmentation and the Circular Hough Transform (CUT). The original edge map of craters is detected by canny operator. In most literatures Hough transform is generally used for crater detection but we have added a shadow removal which includes a novel color image fusion method, based on the multi-scale Retinex (MSR) and discrete wavelet transform (DWT), is proposed. This proposed method is capable of detecting partially visible craters, and overlapping craters.

关键词： feature extraction shadow removal multi-scale Retinex discrete wavelet transform image segmentation circular hough transform

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Fuzzy Soft Thresholding Based Hybrid Denoising Model

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Roy, Sudipta Sinha, Nidul Sen, Asoke Kr. Assam Univ Dept IT Silchar 788011 Assam India NIT Dept Elect Engn Silchar 788010 Assam India Assam Univ Dept Phys Silchar 788011 Assam India

ISBN: (纸本)9783642240546;9783642240553

This paper proposes a denoising model hybridized using wavelet and bilateral filters with fuzzy soft thresholding. The parameters of the proposed model are optimized with floating point genetic algorithm (FPGA). The model optimized with one image is used as a general denoising model for other images like Lena, Fetus, Ultrasound, Xray, Baboon, and Zelda. The performance of the proposed model is evaluated in denoising images injected with noises in different degrees;moderate, high and very high, and the results obtained are compared with those obtained with similar hybrid model with wavelet soft thresholding. Results demonstrate that the performance of the proposed model in terms of PSNR and IQI in denoising most of the images is far better than those with similar model with wavelet soft thresholding. It has also been observed that the hybrid model with wavelet soft thresholding fails to denoise images with very high degree of noises while the proposed model can still be capable of denoising.

关键词： image denoising fuzzy soft thresholding wavelet thresholding bilateral filter

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A Comparative study on Human Spermatozoa images Classification with Artificial Neural Network Based on FOS, GLCM and Morphological Features

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Abbiramy, V. S. Tamilarasi, A. Velammal Engn Coll Madras Tamil Nadu India Kongu Engn Coll Perundurai India

ISBN: (纸本)9783642240546;9783642240553

This paper aims to evaluate the accuracy of artificial neural network based classifiers using human spermatozoa images. Three different neural network based classifiers are used: Feed Forward Neural Network, Radial Basis Neural Network and Elman Back Propagation Neural Network. These three different classifiers were investigated to determine their ability to classify various categories of human spermatozoa images. The investigation was performed on the basis of the different feature vectors. The feature vector includes first order statistics (FOS), textural and morphological features. The extracted features are then used to train and test the artificial neural network. Experimental results are presented on a dataset of 91 images consisting of 71 abnormal images and 20 normal images. The radial basis network produced the highest classification accuracy of 60%, 75% and 70% when trained with FOS, Combined and Morphological features. When feed forward neural network is trained with GLCM features, a classification accuracy of 75% is achieved.

关键词： Segmentation Gray level Co-occurrence matrix First Order statistics Artificial Neural Network image processing Classification Spermatozoa

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VLSI architecture for compressed domain video watermarking

VLSI architecture for compressed domain video watermarking

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1st international conference on digital image processing and pattern recognition, dppr 2011

作者： Mohankumar, N. Nirmala Devi, M. Badari Nath, D. Scaria, Arun VLSI Design Research Group Department of Electronics and Communication Engineering School of Engineering Coimbatore India

ISBN: (纸本)9783642240546

digital watermarking has become very important for protecting the authenticity of multimedia objects as they become easier to copy, exchange, and modify due to the large diffusion of powerful personal computers. The video has been utilized in a variety of applications such as video editing, Internet video distribution, wireless video communications etc. Some of these applications are likely to get great benefit from video watermarking technology. Main objective of this research is to design robust perceptual video watermarking targeted at achieving better performance and reliability. Due to its robust nature, Discrete Cosine Transform (DCT) watermarking was chosen in this work to accomplish video copyright protection. The watermark is inserted in the video stream during compression, resulting in an optimized compression/watermarking algorithm and system. © 2011 Springer-Verlag.

关键词： image compression

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Unsupervised medical image classification based on skew Gaussian mixture model and hierarchical clustering algorithm

Unsupervised medical image classification based on skew Gaus...

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1st international conference on digital image processing and pattern recognition, dppr 2011

作者： Vadaparthi, Nagesh Yarramalle, Srinivas Suresh Varma, P. Dept. of I.T. M.V.G.R. College of Engineering Vizianagaram India Dept. of IT GITAM University Visakhapatnam India Aadikavi Nannaya University Rajahmundry India

ISBN: (纸本)9783642240546

A novel segmentation algorithm for brain images is proposed using finite skew Gaussian mixture model. Recently, much work has been reported in medical image segmentation. Among these techniques, finite Gaussian mixture models are considered to be more recent and accurate. However, in this approach, a number of segments that an image can be divided are taken through apriori and if these segments are not initiated properly it leads to misclassification. Hence, to overcome this disadvantage, we proposed an algorithm for Medical image Segmentation using Hierarchical Clustering and Skew Gaussian Mixture. The experimentation is done with four different brain images and the results obtained are evaluated using Quality metrics. © 2011 Springer-Verlag.

关键词： Gaussian distribution

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Iris liveness detection for semi-transparent contact lens spoofing

Iris liveness detection for semi-transparent contact lens sp...

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1st international conference on digital image processing and pattern recognition, dppr 2011

作者： Puhan, Niladri B. Natarajan, Sudha Suhas Hegde, A. International Institute of Information Technology Bangalore India School of Computer Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9783642240546

Park's proposed liveness detection technique in [5] detects the fake irises by checking the pupil size variation and textural feature change in local iris area. A new semi-transparent contact lens based spoofing method is designed to overcome the liveness technique. The spoofing method generates artificial texture image by replicating imposter's natural iris texture adjacent to pupil boundary. Simulation results show that by printing the artificial texture image on semi-transparent contact lens, an imposter can pass through the liveness detection to illegally make an entry despite being in negative-watch lists. A countermeasure algorithm is suggested for improving the liveness detection technique. © 2011 Springer-Verlag.

关键词： Contact lenses

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Advances in digital image processing and Information Technology: First international conference on digital image processing and pattern recognition, dppr 2011, Tirunelveli, Tamil Nadu, India, September 23-25, 2011 Proceedings

Communications in Computer and Information Science

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Communications in Computer and Information Science 2011年 205 CCIS卷

作者： Nagamalai, Dhinaharan Renault, Eric Dhanuskodi, Murugan Wireilla Net Solutions PTY Ltd Melbourne VIC Australia Samovar UMR INT-CNRS 5157 9 rue Charles Fourier 91011 Evry Cedex France Manonmaniam Sundaranar University Department of Computer Science and Engineering Tirunelveli Tamil Nadu India

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Segmentation of micro calcification clusters in digital mammograms using UIQI

Segmentation of micro calcification clusters in digital mamm...

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1st international conference on digital image processing and pattern recognition, dppr 2011

作者： Chandra Murty, Patnala S. R. Sudheer, T. Sreenivasa Reddy, E. Department of Computer Science and Engg. Acharya Nagarjuna University Guntur A.P. India

ISBN: (纸本)9783642240546

This paper presents a new method for automatic detection of clustered micro calcifications (both malignant and benign) in digitized mammograms. Compared to previous works, the innovation here is that the processing is performed by labeling the texture regions in the original image. This new method uses the labeling the textures of the mammographic images on the basis of UIQI (universal quality index). Once labeling is performed, mammogram is segmented into various regions and further thresholds are used to separate the clustered micro calcifications. By comparing our results with those found in the literature, we proved that the method enormously reduces the computing time as UIQI utilizes simple statistical features like mean, variance and standard deviations only. In this paper, an automatic segmentation and classification of massive lesions in mammographic images is evaluated on Mini-MIAS database consisting 320 digitalized mammograms. Furthermore, classification rates enhancements were also revealed by testing our method compared to existing methods. © 2011 Springer-Verlag.

关键词： Mammography

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stego-image Generator (SIG) - Building steganography image database

Stego-Image Generator (SIG) - Building steganography image d...

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1st international conference on digital image processing and pattern recognition, dppr 2011

作者： Thiyagarajan, P. Aghila, G. Prasanna Venkatesan, V. CDBR-SSE Lab. Department of Computer Science Pondicherry University Puducherry 605 014 India

ISBN: (纸本)9783642240546

Any Universal steganalysis algorithm developed should be tested with various stego-images to prove its efficiency. This work is aimed to develop a tool to build the stego-image database which is obtained by implementing various RGB based Least Significant Bit steganographic algorithms. Though there are many stego-images sources available on the internet it lacks in the information such as how many rows has been infected by the steganography algorithms, how many bits have been modified and which channel has been affected. These parameters are important for steganalysis algorithms to rate its efficiency. For the experiments conducted using proposed method, stego-image image Generator Tool, images are chosen from board categories such as animals, nature, person etc to produce variety of stego-image. The proposed stego-image Generator (SIG) has been compared with various stego-tools against various parameters to prove its efficiency. © 2011 Springer-Verlag.

关键词： steganography

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A new method for lossless image compression using recursive crack coding

A new method for lossless image compression using recursive ...

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1st international conference on digital image processing and pattern recognition, dppr 2011

作者： Meyyappan, T. Thamarai, S.M. Jeya Nachiaban, N.M. Department of Computer Science and Engineering Alagappa University Karaikudi - 630 003 India Department of Computer Science and Engineering Thiagarajar College of Engineering Madurai-9 India

ISBN: (纸本)9783642240546

Popular entropy coding methods for lossless compression of images depend on probability models. They start by predicting the model of the data. The accuracy of this prediction determines the optimality of the compression. These methods are very slow because of visiting the data (pixels) in left to right order. Parallel implementation of these methods is adopted by researchers to speed up the process. In this paper, the authors propose a new approach to image compression using crack coding. The novelty and better compression ratio of the method is due to its recursiveness in finding the variable-length entropy. The proposed method starts with the original image and develop crack codes in a recursive manner, marking the pixels visited earlier and expanding the entropy in four directions. The proposed method is experimented with sample bitmap images and results are encouraging. The method is implemented in uni-processor machine using C language source code. © 2011 Springer-Verlag.

关键词： Entropy

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