{"title":"Variational segmentation of color images","authors":"N. Nasios, A. Bors","doi":"10.1109/ICIP.2005.1530130","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1530130","url":null,"abstract":"A variational Bayesian framework is employed in the paper for image segmentation using color clustering. A Gaussian mixture model is used to represent color distributions. Variational expectation-maximization (VEM) algorithm takes into account the uncertainty in the parameter estimation ensuring a lower bound on the approximation error. In the variational Bayesian approach we integrate over distributions of parameters. The processing task in this case consists of estimating the hyperparameters of these distributions. We propose a maximum log-likelihood initialization approach for the variational expectation-maximization (VEM) algorithm. The proposed algorithm is applied to image segmentation using color clustering when representing the images in the L*u*v color coordinate system.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117297831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Video compression using blur compensation","authors":"M. Budagavi","doi":"10.1109/ICIP.2005.1530197","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1530197","url":null,"abstract":"Traditional block-based motion compensation techniques such as those used in the H.264 video coding standards become ineffective when blurring starts to occur in the video sequence. Blurring typically occurs in video sequences when the relative motion between the camera and the scene being captured is faster than the camera exposure time. Blurring is also sometimes used as a special effect for smoothly transitioning between scenes in a movie. Blurring also naturally occurs when objects at different depths in a scene are focused and defocused in a video sequence. In this paper, we propose the blur compensation algorithm that makes use of the blurring information to provide improved compression performance when compared to H.264 in the presence of blur in video sequences. When coding blurred scenes in video sequences, bitrate reductions of up to 64% were achieved.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129545332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Low-resolution photo/drawing classification: metrics, method and archiving optimization","authors":"S. Simske","doi":"10.1109/ICIP.2005.1530110","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1530110","url":null,"abstract":"Archiving and re-purposing are automated using zoning analysis that performs segmentation (region boundary definition), classification (region typing) and bit-depth determination. For performance throughput reasons, zoning analysis is often performed on a low-resolution (e.g. 50-100 ppi) representation of the document. At these resolutions, heuristic metrics for classification are required. Reported here are metrics for distinguishing photos and color drawings, and a novel classification technique based solely on the statistics of each heuristic metric. The statistical technique allows ready combination of multiple binary classifiers, and provides a lower classification error than simple voting or metric-confidence techniques. This technique permits new metrics to improve the overall classification. The benefit of this technique on archival optimization is shown.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129750899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unsupervised style classification of document page images","authors":"Song Mao, Lan Nie, G. Thoma","doi":"10.1109/ICIP.2005.1530104","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1530104","url":null,"abstract":"Style classification of document page images is crucial for logical structure analysis of heterogeneous collections of documents. Both layout and contextual features contain significant information about document styles. Most existing methods are supervised methods in which specific document models or classifiers are learned from a training set of document page images with known class labels. In this paper, we propose an unsupervised classification method that involves no training or manual selection of algorithm parameters. In particular, we first represent each document page as an ordered labeled X-Y tree. A tree matching algorithm is then used to compute style dissimilarity between two document pages. We propose a set of tree edit cost functions based on Karl Pearson distance between two multivariate feature observations, which is robust to the over-segmentation problem and zone length variations of same logical entities. Finally, the K-medoids algorithm is used to find an optimal grouping of the trees into K clusters, each of which corresponds to a distinct document style. We evaluate our algorithm on test datasets with different cluster sizes and degrees of style similarity. Experimental results show our algorithm achieved an average classification accuracy of 95.69% over six datasets consisting of 150 pages of 11 different styles.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128547585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reversible image rotations with modulo transforms","authors":"S. Srinivasan","doi":"10.1109/ICIP.2005.1530010","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1530010","url":null,"abstract":"This paper proposes a new paradigm for the construction of reversible two point transforms or planar rotations. We show that the transform coefficients for integer to integer mappings through an integer rotation matrix are redundant in modular arithmetic. This redundancy can be exploited by quantizing transform coefficients in a critical manner, producing reversible and unit determinant transforms. For a subset of such critically quantized transforms, the quantization process can be performed by rounded integer division along each dimension. Such transforms are formed by a subset of Pythagorean triads, and can be used to implement reversible image rotations from a countable set of rotation angles. The subjective quality of the rotation so obtained compares favorably with the three shear or lifting algorithm.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128597349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Geometric skeletonization using the symmetry set","authors":"Arjan Kuijper, O. F. Olsen","doi":"10.1109/ICIP.2005.1529796","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529796","url":null,"abstract":"In this paper we present a novel method to derive the skeleton of a shape by means of its symmetry set. We use the property that the medial axis is a subset of the symmetry set. This set is obtained as zero crossings of two equations, based on geometric arguments. The resulting skeleton can easily be annotated with respect to main axis and branches, since this information follows directly from the symmetry set.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128717416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A cross-layer approach for energy efficient transmission of progressively coded images over wireless channels","authors":"C. Costa, F. Granelli, A. Katsaggelos","doi":"10.1109/ICIP.2005.1529725","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529725","url":null,"abstract":"Mobility, made available by today's communication networks, imposes several limitations in the design of multimedia applications, due to high error rates, reduced bandwidth, strong variability, and mobile terminals lifetime. This paper investigates the use of an energy constrained cross-layer approach for the transmission of progressively coded images over packet-based wireless channels. We propose an optimum power allocation algorithm to enable unequal error protection of a pre-encoded image. Simulations are performed modeling transmission over a Rayleigh fading channel. The investigation focuses on JPEG2000, but it is applicable to other progressively coded bitstreams as well. Our experimental results demonstrate that it is possible to achieve a relevant performance enhancement with the proposed approach over uniform error protection. The optimal solution can also serve as a guideline for developing less computationally intensive empiric approaches.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126984027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiple active contour models based on the EM algorithm","authors":"M. Silveira, J. Marques","doi":"10.1109/ICIP.2005.1529743","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529743","url":null,"abstract":"This paper describes an algorithm for the extraction of multiple regions using multiple active contour models (ACMs). The algorithm organizes edge points into strokes and assigns a set of weights summing to one to each stroke. These weights represent the soft assignment of the stroke to each of the ACMs and depend on the distance between the stroke points and the ACM units. Both the weights and the ACMs energy minimization are computed using the expectation-maximization (EM) algorithm. The algorithm described in this paper is an extension of the adaptive snakes recently proposed in Nascimento, JC and Marques, JS (2003). Experimental results are provided to illustrate the performance of the proposed algorithm.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127015891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of semantic objects using description graphs","authors":"Xavier Giro-i-Nieto, F. Marqués","doi":"10.1109/ICIP.2005.1529972","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529972","url":null,"abstract":"This paper presents a technique to detect instances of classes (objects) according to their semantic definition in the form of a description graph. Classes are defined as combinations of instances of lower level semantic classes and allow the definition of a semantic tree that organizes classes in semantic levels. At the bottom level of the semantic tree, classes are defined by a perceptual model containing a list of low-level descriptors. The proposed detection algorithm follows a bottom-up/top-down approach, building semantic trees on a region-based representation of the media. The flexibility of the approach is assessed on different examples of planar objects, such as frontal faces, groups of islands, flags and traffic signs.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123951799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Error accumulation in multiple cycles of still image compression and color transformations","authors":"M. Domański, Krzysztof Rakowski","doi":"10.1109/ICIP.2005.1529874","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529874","url":null,"abstract":"The problem of error accumulation in consecutive compression/decompression cycles of still images is discussed in this article. Considered are predictive and transform techniques together with color transformations. Theoretical analysis is provided for error accumulation in linear transformations followed by quantization. The conditions for lack of error accumulation are discussed. This theoretical analysis is applied to color transformations and compression cycles. Experimental analysis verifies theoretical results and deals with more complicated cases. The experimental analysis includes lossy and near lossless compression as well as color transformations themselves. Moreover, a new technique of near lossless compression with no error accumulation is proposed.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124206221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}