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33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)最新文献

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Visual adaptation of scale and imprecision in a noisy world 在嘈杂的世界中对尺度和不精确的视觉适应
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.49
M. H. Brill
{"title":"Visual adaptation of scale and imprecision in a noisy world","authors":"M. H. Brill","doi":"10.1109/AIPR.2004.49","DOIUrl":"https://doi.org/10.1109/AIPR.2004.49","url":null,"abstract":"Pointlike quantum noise in an image can be defeated either by representing the image at a low gray-scale resolution or at a low spatial resolution. The first solution locates an image at an inherent imprecision, and the second locates the image at an inherent spatial scale. Two vision-based models combat noise by automatic and local spatial-scale adjustment. Making contrast steps proportional to the square root of intensity (the deVries-Rose law) uses the imprecision solution. A hybrid system such as human vision use both spatial solutions, and also carries out similar processing in the time domain.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130037836","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}
引用次数: 0
Top-down approach to segmentation of prostate boundaries in ultrasound images 超声图像中前列腺边界的自顶向下分割方法
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.46
A. Jendoubi, J. Zeng, M. Chouikha
{"title":"Top-down approach to segmentation of prostate boundaries in ultrasound images","authors":"A. Jendoubi, J. Zeng, M. Chouikha","doi":"10.1109/AIPR.2004.46","DOIUrl":"https://doi.org/10.1109/AIPR.2004.46","url":null,"abstract":"Ultrasound has been increasingly used in surgical procedures of the prostate in recent years. Segmentation of prostate boundaries from ultrasound images is clinically useful in such situations as accurate volume measurement, and tumor margin estimation, and it can also provide real-time targeted image guidance during procedures such as biopsy and ablation. Automatic segmentation of the prostate, however, is a challenging task since the ultrasound images usually have high level of speckle noises due to large amount of random scatters and thus they have a very low signal-to-noise ratio. As a result, physicians have to use manual methods to draw contours of the prostate, slice by slice, in order to calculate prostate volume information. This is a tedious work and apparently it delays the whole clinical procedures. In addition, accuracy of the segmented prostate boundaries cannot be guaranteed due to significant variations among different physicians or with the same physician at different times. In this paper, we present a top-down approach to the segmentation of prostate ultrasound images using a snake model, as compared to most existing bottom-up methods. Special measures were taken to deal with the high speckle noises and complex shapes of prostate boundaries. In general, median filtering proved to be effective in removing speckle noises. We extensively evaluated most of the existing edge detection methods and found that the logic combination of Laplacian of Gaussian (LoG) and Sobel operator provided the best performance in finding the useful image gradients. Parameters of the snake were dynamically optimized, and the shape information of the prostate was used as a strong guidance during the deformation process of the snake model. Experimental results with several ultrasound prostate images with various levels of noises were presented to demonstrate the effectiveness of the proposed approach.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115105788","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}
引用次数: 16
Swarmed feature selection 蜂群特征选择
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.41
H. Firpi, E. Goodman
{"title":"Swarmed feature selection","authors":"H. Firpi, E. Goodman","doi":"10.1109/AIPR.2004.41","DOIUrl":"https://doi.org/10.1109/AIPR.2004.41","url":null,"abstract":"Feature selection is an important part of pattern recognition, helping to overcome the curse of dimensionality problem with classifiers, among other systems. In this work, we introduce a feature selection method using particle swarm optimization. Experiments using data of others and hyperspectral remote sensed data are used to measure the performance of the algorithm. Its comparison with a genetic algorithm is also shown.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125642478","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}
引用次数: 104
NaviGaze: enabling access to digital media for the profoundly disabled NaviGaze:使重度残疾人能够访问数字媒体
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.33
Ryan O'Grady, C. Cohen, G. Beach, G. Moody
{"title":"NaviGaze: enabling access to digital media for the profoundly disabled","authors":"Ryan O'Grady, C. Cohen, G. Beach, G. Moody","doi":"10.1109/AIPR.2004.33","DOIUrl":"https://doi.org/10.1109/AIPR.2004.33","url":null,"abstract":"Graphical interfaces have become dominant in today's computer environment. These interfaces typically consist of windows, icons, menus, and buttons that require the use of some continuous-input pointing device. Common examples of these devices include mice, styli, trackballs, touchpads, and joysticks. However, all of these devices are designed to be controlled by the user's hands. This places people who can't use their hands (amputees, quadriplegics, those with muscular disorders) at a serious disadvantage in using the computer. Therefore, there is a need for systems capable of controlling the mouse pointer without requiring hand manipulation. Because many disabled people still have significant control of their head motion, head tracking is a logical choice. We have developed a non-intrusive head tracking system for cursor control, coupled with eye blink recognition to emulate mouse clicking. The system, called NaviGaze, still allows the use of a standard mouse and keyboard, making it ideal for use in public computing environments.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132198860","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}
引用次数: 6
Complex neural networks as future tools in imagery analysis 作为未来图像分析工具的复杂神经网络
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.19
O. Sporns
{"title":"Complex neural networks as future tools in imagery analysis","authors":"O. Sporns","doi":"10.1109/AIPR.2004.19","DOIUrl":"https://doi.org/10.1109/AIPR.2004.19","url":null,"abstract":"Brain networks are uniquely capable of generating and integrating information collected from multiple sources in real time. The application of structural and information theoretical measures to such networks has begun to unravel the crucial ingredients that ensure their rapid and robust performance. We suggest the use of information theoretical measures in applications that mimic some of these biological processing principles. We discuss candidate measures, their implementation in neural networks, their applicability to various sets of artificial and natural stimuli, and their future use in the automated analysis of aerial images.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128090411","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}
引用次数: 1
Feasibility study for the development of a motion imagery quality metric 运动图像质量度量发展的可行性研究
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.25
J. Irvine, C. Fenimore, David M. Cannon, J. Roberts, S. Israel, L. Simon, C. Watts, James D. Miller, Michelle Brennan, A. Avilés, Paul F. Tighe, Richard J. Behrens
{"title":"Feasibility study for the development of a motion imagery quality metric","authors":"J. Irvine, C. Fenimore, David M. Cannon, J. Roberts, S. Israel, L. Simon, C. Watts, James D. Miller, Michelle Brennan, A. Avilés, Paul F. Tighe, Richard J. Behrens","doi":"10.1109/AIPR.2004.25","DOIUrl":"https://doi.org/10.1109/AIPR.2004.25","url":null,"abstract":"In this evaluation, a number of experienced imagery analysts provided ratings and comparisons of a number of motion imagery clips and images derived from these clips. The image set was well characterized in terms of target motion, camera motion, and scene complexity, as well as ground sampled distance (GSD). Analysis of the data from this evaluation provides insight into the magnitude of these effects on perceived image interpretability. This paper describes the evaluation, presents the results, and explores the implications for development of a \"NIIRS-like\" scale for motion imagery.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123145280","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}
引用次数: 13
Minimizing uncertainty in determinants and ratios of determinants for invariant relationships employed in SAR imagery pattern recognition 最小化SAR图像模式识别中不变量关系的决定因素和决定因素比例的不确定性
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.29
Lewis Reynolds, W. Kober
{"title":"Minimizing uncertainty in determinants and ratios of determinants for invariant relationships employed in SAR imagery pattern recognition","authors":"Lewis Reynolds, W. Kober","doi":"10.1109/AIPR.2004.29","DOIUrl":"https://doi.org/10.1109/AIPR.2004.29","url":null,"abstract":"Invariant relationships involving ratios of determinants have been proposed for the classification of an object in SAR imagery. The target detection decision-making process depends on the uncertainty involved in the measurements. At fixed experimental resolution, some determinants are simply better than others because they are much less sensitive to uncertainty. A geometrical interpretation of determinants is applied to assess the minimum relative uncertainty expected for a determinant employed in invariant relationships. Because much larger relative uncertainties can occur in some determinants, a method based on the perturbation of eigenvalues is proposed to identify determinants that are less sensitive to element errors. Symmetric alpha-stable probability distribution functions are employed to characterize error distributions in ratios of determinants.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131967860","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}
引用次数: 0
Computation in the higher visual cortices: map-seeking circuit theory and application to machine vision 高级视觉皮层的计算:寻图电路理论及其在机器视觉中的应用
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.20
D. Arathorn
{"title":"Computation in the higher visual cortices: map-seeking circuit theory and application to machine vision","authors":"D. Arathorn","doi":"10.1109/AIPR.2004.20","DOIUrl":"https://doi.org/10.1109/AIPR.2004.20","url":null,"abstract":"Map-seeking circuit theory is a biologically based computational theory of vision applicable to difficult machine vision problems such as recognition of 3D objects in arbitrary poses amid distractors and clutter, as well as to non-recognition problems such as terrain interpretation. It provides a general computational mechanism for tractable discovery of correspondences in massive transformation spaces by exploiting an ordering property of superpositions. The latter allows a set of transformations of an input image to be formed into a sequence of superpositions which are then \"culled\" to a composition of single mappings by a competitive process which matches each superposition against a superposition of inverse transformations of memory patterns. The architecture that performs this is based on a number of neuroanatomical features of the visual cortices, including reciprocal dataflows and inverse mappings.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115352481","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}
引用次数: 20
Embedded reading device for blind people: a user-centered design 嵌入式盲人阅读设备:以用户为中心的设计
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.22
J. Peters, C. Mancas-Thillou, Silvio Ferreira
{"title":"Embedded reading device for blind people: a user-centered design","authors":"J. Peters, C. Mancas-Thillou, Silvio Ferreira","doi":"10.1109/AIPR.2004.22","DOIUrl":"https://doi.org/10.1109/AIPR.2004.22","url":null,"abstract":"A handheld PDA-based system is being developed to help blind people in their daily tasks. The design combines in a continuous process users' involvement and engineers' effort. This interaction is made efficient thanks to a specialist able to communicate with both parties and to extract useful knowledge for them. The system can be viewed as a main loop including the user taking the snapshot, text/picture detection, optical character recognition, text-to-speech synthesis, feedback to the user, until a useful output is reached. Each task is carried out by algorithms integrating both technical performance and user requirements.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122025431","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}
引用次数: 26
An image retrieval system using multispectral random field models, color, and geometric features 一个使用多光谱随机场模型、颜色和几何特征的图像检索系统
33rd Applied Imagery Pattern Recognition Workshop (AIPR'04) Pub Date : 2004-10-13 DOI: 10.1109/AIPR.2004.13
O. Hernandez, A. Khotanzad
{"title":"An image retrieval system using multispectral random field models, color, and geometric features","authors":"O. Hernandez, A. Khotanzad","doi":"10.1109/AIPR.2004.13","DOIUrl":"https://doi.org/10.1109/AIPR.2004.13","url":null,"abstract":"This paper describes a novel color texture-based image retrieval system for the query of an image database to find similar images to a target image. The retrieval process involves segmenting the image into regions of uniform color texture using an unsupervised histogram clustering approach that utilizes the combination of multispectral simultaneous auto regressive (MSAR) and color features. The color texture content, location, area and shape of the segmented regions are used to develop similarity measures describing the closeness of a query image to database images. These attributes are derived from the maximum fitting square and best fitting ellipse to each of the segmented regions. The proposed similarity measure combines all these attributes to rank the closeness of the images. The performance of the system is tested on two databases containing synthetic mosaics of natural textures and natural scenes, respectively.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129392135","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}
引用次数: 0
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