{"title":"Image segmentation techniques for object-based coding","authors":"Junaid Ahmed, J. Bosworth, S. Acton","doi":"10.1109/IAI.2000.839568","DOIUrl":"https://doi.org/10.1109/IAI.2000.839568","url":null,"abstract":"Two image segmentation methods are presented and compared terms of rate-distortion within an object-based coding scheme. The LOMO segmentation exploits the relationship between mathematical morphology and local monotonicity in producing a multiscale segmentation. The process is a morphological analogy to the Laplacian of Gaussian. The level set approach used area morphology to generate segmented regions having a specified minimum area. Segments are optimally chosen from the connected components of the image level sets. A simple object-based coding scheme using the discrete cosine transform is used to avoid the artifacts produced by conventional block-based coding at segment boundaries. Results of each segmentation method are given and compared to another and to conventional JPEG coding by rate-distortion and the presence of boundary artifacts.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129620360","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":"Using deformable models to segment complex structures under geometric constraints","authors":"C. Gout, S. Vieira-Testé","doi":"10.1109/IAI.2000.839580","DOIUrl":"https://doi.org/10.1109/IAI.2000.839580","url":null,"abstract":"In many problems of medical or geophysical interest, when trying to segment an image, one has to deal with data that exhibit very complex structures. This problem occurs when images have discontinuities: in medical imaging (fractures radiography), in geophysics (segmentation of a set of layers and faults) etc. To solve this problem, we present a segmentation method which uses deformable models. The originality of the method is that we have interpolation data and triple points that involves making some geometric constraints on the model. We also propose a method for noise removal because it is well known that most of these images are noisy, that could hinder the segmentation. Numerical results on geophysical images are given.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122217967","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}
Jesús Bescós, J. Sanchez, Julián Cabrera, J. Menéndez, Guillermo Cisneros
{"title":"Gradual shot transition detection based on multidimensional clustering","authors":"Jesús Bescós, J. Sanchez, Julián Cabrera, J. Menéndez, Guillermo Cisneros","doi":"10.1109/IAI.2000.839570","DOIUrl":"https://doi.org/10.1109/IAI.2000.839570","url":null,"abstract":"Detection of shot transitions in video material is a process intended to ease the automatic extraction of video features for later use in indexing and retrieval purposes. While abrupt shot transitions are discontinuities quite easy to detect, the gradual ones are highly masked by and confused with object motion, camera operation, and other disturbing effects. Current approaches to detecting gradual transitions are based on the calculation of several inter-frame distances, and on the compensation and detection of the aforementioned causes of disturbance. This article presents an innovative detection method based on a multi-parameter modeling of the patterns that these transitions produce over a simple inter-frame distance, which opens the possibility of a later multi-dimensional classification of the desired transitions into a single cluster.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133384493","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 thinning algorithm for digital figures of characters","authors":"Michio Shimizu, Hiroshi Fukuda, G. Nakamura","doi":"10.1109/IAI.2000.839576","DOIUrl":"https://doi.org/10.1109/IAI.2000.839576","url":null,"abstract":"A thinning scheme could be used as a useful method of pre-processing in image processing. Various algorithms have been proposed to produce the skeleton of a digital binary pattern. However, they have undesirable properties that tend to cause shrinking or vanishing of segments, the appearance of a beard, and warping where segments intersect. In this paper, we propose a parallel Hilditch algorithm to acquire a more stable output. In particular, we introduce two kinds of masks that are effective in the thinning of digital figures of characters. Then, we evaluate the performance of our scheme by investigating thinning for 432 kinds of commonly used character fonts. We conclude that the skeletons obtained from our method give better results than those of any other major thinning algorithms.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123356343","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":"An efficient adaptive KLT for multispectral image compression","authors":"Lena Chang, Ching-Min Cheng, Ting-Chung Chen","doi":"10.1109/IAI.2000.839610","DOIUrl":"https://doi.org/10.1109/IAI.2000.839610","url":null,"abstract":"In the study, we present an efficient adaptive Karhunen-Loeve transform (KLT) algorithm for multispectral image compression. The proposed algorithm fully exploits the spectral and spatial correlation in the data. To adopt to the local terrain characteristics of multispectral images, the adaptive KLT algorithm can divide the original image into some proper regions, and transform each region image data set by the corresponding transformation function. Furthermore, the algorithm is suitable for hardware implementation. Simulation results show that the performance of the proposed adaptive KLT algorithm is better than those of the existing algorithms.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116151476","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}
G. Christensen, P. Yin, M. Vannier, K. Chao, J. Dempsey, J. Williamson
{"title":"Large-deformation image registration using fluid landmarks","authors":"G. Christensen, P. Yin, M. Vannier, K. Chao, J. Dempsey, J. Williamson","doi":"10.1109/IAI.2000.839614","DOIUrl":"https://doi.org/10.1109/IAI.2000.839614","url":null,"abstract":"For each patient receiving definitive treatment for cervix cancer, several CT/MR imaging studies need to be registered in order to specify the total physical or biological dose to each fixed tissue voxel in an organ system. This turns out to be a difficult problem due to large localized deformations and displacements of bladder, rectum, vagina, uterus and paracervical tissues due to tumor regression, bladder and rectal filling variations, and especially insertion of the applicator itself. This paper explores the utility of using the fluid landmark image registration method to register images before and after insertion of the brachytherapy applicator in order to track radiation dose from one treatment to the next.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124531080","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":"Hybrid hidden Markov model for face recognition","authors":"H. Othman, T. Aboulnasr","doi":"10.1109/IAI.2000.839567","DOIUrl":"https://doi.org/10.1109/IAI.2000.839567","url":null,"abstract":"In this paper, we introduce a hybrid hidden Markov model (HMM) face recognition system. The proposed system contains a low-complexity 2D HMM-based face recognition (LC 2D-HMM FR) module that carries out a complete search in the compressed domain followed by a 1D HMM-based face recognition (1D-HMM FR) module which refines the search based on a candidate list provided by the first module. We also examine a remote database search methodology that may be helpful for accessing remote resources, where no prior information is assumed regarding the contents of the remote database. The performance of the hybrid HMM face recognition system is reported for both local and remote database search modes.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114609889","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":"Improved accuracy for interferometric radar images using polarimetric radar and laser altimetry data","authors":"K. C. Slatton, M. Crawford, B. L. Evans","doi":"10.1109/IAI.2000.839591","DOIUrl":"https://doi.org/10.1109/IAI.2000.839591","url":null,"abstract":"The ability to measure land surface topography over large areas to assess natural hazard threats posed by seismic and flooding events is a critical international need. Interferometric synthetic aperture radar (INSAR) has been used to map topography; however, accuracies are limited because observations are not measurements of true surface topography over vegetated areas. Instead, the measurements, which depend on the sensor and the vegetation, represent some height above the true surface. We develop a two-step correction for the INSAR imagery to account for penetration into the vegetation. The INSAR imagery is first adaptively filtered to reduce random measurement noise. We then combine the INSAR with polarimetric radar and laser altimetry data to account for the vegetation contribution to the topographic heights.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127362197","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":"Foveated video image analysis and compression gain measurements","authors":"Sanghoon Lee, A. Bovik","doi":"10.1109/IAI.2000.839572","DOIUrl":"https://doi.org/10.1109/IAI.2000.839572","url":null,"abstract":"We present a framework for assessing the quality of, and determining the efficiency of foveated and compressed images and video streams. We develop unique algorithms for assessing the quality of foveated image/video data. By interpreting foveation as a coordinate transformation, we analyze the increase in compression efficiency that is afforded by our foveation approach. We demonstrate these concepts on foveated, compressed video streams using modified (foveated) versions of H.263 that are standards-compliant. In the simulations, quality versus compression is enhanced considerably by the foveation approach. We obtain compression gains ranging from 8% to 52% for I pictures and from 7% to 68% for P pictures.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129206164","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":"Multiresolution hidden Markov chain model and unsupervised image segmentation","authors":"L. Fouque, A. Appriou, W. Pieczynski","doi":"10.1109/IAI.2000.839584","DOIUrl":"https://doi.org/10.1109/IAI.2000.839584","url":null,"abstract":"Several approaches have been proposed in the last few years to handle the problem of multiresolution image segmentation. In a Bayesian framework, models using Markov fields have been highly effective. However the computational cost can be prohibitive. Markov tree models were therefore proposed. Although fast, these methods do not always give good results. In this article, we propose a new approach using a Markov chain built by transforming multiresolution images into one vectorial process via a Peano type scan, the Hilbert scan. We work in an unsupervised context in which parameter estimation is carried out by using a mixture distribution algorithm, the ICE algorithm. Experimental results, including classification of multiresolution synthetic images and SPOT images, are presented in this paper.","PeriodicalId":224112,"journal":{"name":"4th IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"86 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128855773","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}