Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234085
D. Riccio, M. Nappi
Fractals are a promising framework for several applications other than image coding and transmission, such as database indexing, texture mapping and pattern recognition problems such as writer authentication. However, fractal based algorithms are strongly asymmetric because, in spite of the linearity of the decoding phase, the coding process is very time consuming. Many different solutions have been proposed for this problem, but there is not yet a standard for fractal coding. In this paper we analyze the problem of complexity reduction of the image coding phase and providing a new classification technique based on an approximation error measure. We show formally that postponing range/domain comparisons with respect to a preset block, it is possible to reduce the amount of operations needed to encode each range and therefore whole the image. The proposed strategy allows a drastic complexity reduction of the coding phase. The proposed method has been compared with another fractal coding method, showing in which circumstances the proposed algorithm performs better in terms of both bit rate and/or computing time.
{"title":"Deferring range/domain comparisons in fractal image compression","authors":"D. Riccio, M. Nappi","doi":"10.1109/ICIAP.2003.1234085","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234085","url":null,"abstract":"Fractals are a promising framework for several applications other than image coding and transmission, such as database indexing, texture mapping and pattern recognition problems such as writer authentication. However, fractal based algorithms are strongly asymmetric because, in spite of the linearity of the decoding phase, the coding process is very time consuming. Many different solutions have been proposed for this problem, but there is not yet a standard for fractal coding. In this paper we analyze the problem of complexity reduction of the image coding phase and providing a new classification technique based on an approximation error measure. We show formally that postponing range/domain comparisons with respect to a preset block, it is possible to reduce the amount of operations needed to encode each range and therefore whole the image. The proposed strategy allows a drastic complexity reduction of the coding phase. The proposed method has been compared with another fractal coding method, showing in which circumstances the proposed algorithm performs better in terms of both bit rate and/or computing time.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"92 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114160991","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234064
E. Ardizzone, R. Pirrone, O. Gambino
A novel approach to the detection of multiple sclerosis (MS) lesions is presented, which uses an adaptive formulation of the anisotropic diffusion and fuzzy-c-means (FCM) clustering. In opposition to previous works of the same authors, FCM runs only on PD weighted slices that, for each examination, are composed in a unique data set. Images are preprocessed with an an isotropic diffusion filter whose diffusion function has been adaptively optimized to aggregate pixels belonging to lesions and cut off all the others. Adaptivity is used to achieve significant noise reduction. A detailed description of the proposed approach is presented, along with first experimental results.
{"title":"Automatic segmentation of MR images based on adaptive anisotropic filtering","authors":"E. Ardizzone, R. Pirrone, O. Gambino","doi":"10.1109/ICIAP.2003.1234064","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234064","url":null,"abstract":"A novel approach to the detection of multiple sclerosis (MS) lesions is presented, which uses an adaptive formulation of the anisotropic diffusion and fuzzy-c-means (FCM) clustering. In opposition to previous works of the same authors, FCM runs only on PD weighted slices that, for each examination, are composed in a unique data set. Images are preprocessed with an an isotropic diffusion filter whose diffusion function has been adaptively optimized to aggregate pixels belonging to lesions and cut off all the others. Adaptivity is used to achieve significant noise reduction. A detailed description of the proposed approach is presented, along with first experimental results.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133749556","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234063
R. Hult
This paper presents an algorithm that continues segmentation from a semi automatic artificial neural network (ANN) segmentation of the Hippocampus of registered T1-weighted and T2-weighted MRI data. Due to the morphological complexity of the Hippocampus and difficulty of separating from adjacent structures, reproducible segmentation using MR imaging is complicated. The human intervention in the ANN approach, consists of selecting a bounding-box. Grey-level dilated and grey-level eroded versions of the T1-weighted and T2-weighted data are used to minimise leaking from Hippocampus to surrounding tissue combined with possible foreground tissue. The segmentation algorithm uses a histogram-based method to find accurate threshold values. Grey-level morphology is a powerful tool to break stronger connections between the Hippocampus and surrounding regions than is otherwise possible. The method is 3D in the sense that all grey-level morphology operations use a 3 /spl times/ 3 /spl times/ 3 structure element and the herein described algorithms are applied in the three directions, sagittal, axial, and coronal, and the result are then combined together.
{"title":"Grey-level morphology combined with an artificial neural networks approach for multimodal segmentation of the Hippocampus","authors":"R. Hult","doi":"10.1109/ICIAP.2003.1234063","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234063","url":null,"abstract":"This paper presents an algorithm that continues segmentation from a semi automatic artificial neural network (ANN) segmentation of the Hippocampus of registered T1-weighted and T2-weighted MRI data. Due to the morphological complexity of the Hippocampus and difficulty of separating from adjacent structures, reproducible segmentation using MR imaging is complicated. The human intervention in the ANN approach, consists of selecting a bounding-box. Grey-level dilated and grey-level eroded versions of the T1-weighted and T2-weighted data are used to minimise leaking from Hippocampus to surrounding tissue combined with possible foreground tissue. The segmentation algorithm uses a histogram-based method to find accurate threshold values. Grey-level morphology is a powerful tool to break stronger connections between the Hippocampus and surrounding regions than is otherwise possible. The method is 3D in the sense that all grey-level morphology operations use a 3 /spl times/ 3 /spl times/ 3 structure element and the herein described algorithms are applied in the three directions, sagittal, axial, and coronal, and the result are then combined together.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134036662","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234084
A. Marco
Naming image compression's state of the art surely leads to JPEG2000. This new format takes advantage of the discrete wavelet transform to overtake all the compression methods that have been used up to now. This article proposes two changes in the processing chain to deal with sparse histogram images: one nested in Tier-1 coding, the other between coefficient coding and MQ-coder.
{"title":"Working with JPEG2000: two proposals for sparse histogram images","authors":"A. Marco","doi":"10.1109/ICIAP.2003.1234084","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234084","url":null,"abstract":"Naming image compression's state of the art surely leads to JPEG2000. This new format takes advantage of the discrete wavelet transform to overtake all the compression methods that have been used up to now. This article proposes two changes in the processing chain to deal with sparse histogram images: one nested in Tier-1 coding, the other between coefficient coding and MQ-coder.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"310 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116758834","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234088
D. Toth, T. Aach
Object recognition, i.e. classification of objects into one of several known object classes, generally is a difficult task. In this paper we address the problem of detecting and classifying moving objects in image sequences from traffic scenes recorded with a static camera. In the first step, a statistical, illumination invariant motion detection algorithm is used to produce binary masks of the scene-changes. Next, Fourier descriptors of the shapes from the refined masks are computed and used as feature vectors describing the different objects in the scene. Finally, a feedforward neural net is used to distinguish between humans, vehicles, and background clutter.
{"title":"Detection and recognition of moving objects using statistical motion detection and Fourier descriptors","authors":"D. Toth, T. Aach","doi":"10.1109/ICIAP.2003.1234088","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234088","url":null,"abstract":"Object recognition, i.e. classification of objects into one of several known object classes, generally is a difficult task. In this paper we address the problem of detecting and classifying moving objects in image sequences from traffic scenes recorded with a static camera. In the first step, a statistical, illumination invariant motion detection algorithm is used to produce binary masks of the scene-changes. Next, Fourier descriptors of the shapes from the refined masks are computed and used as feature vectors describing the different objects in the scene. Finally, a feedforward neural net is used to distinguish between humans, vehicles, and background clutter.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123814591","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234075
Akihiko Nakagawa, Andrea Kutics, Kiyotaka Tanaka, Masaomi Nakajima
The paper presents a novel approach for image retrieval by combining textual and object-based visual features in order to reduce the inconsistency between the subjective user's similarity interpretation and the retrieval results produced by objective similarity models. A novel multi-scale segmentation framework is proposed to detect prominent image objects. These objects are clustered according to their visual features and mapped to related words determined by psychophysical studies. Furthermore, a hierarchy of words expressing higher-level meaning is determined on the basis of natural language processing and user evaluation. Experiments conducted on a large set of natural images showed that higher retrieval precision in terms of estimating user retrieval semantics could be achieved via this two-layer word association and also by supporting various query specifications and options.
{"title":"Combining words and object-based visual features in image retrieval","authors":"Akihiko Nakagawa, Andrea Kutics, Kiyotaka Tanaka, Masaomi Nakajima","doi":"10.1109/ICIAP.2003.1234075","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234075","url":null,"abstract":"The paper presents a novel approach for image retrieval by combining textual and object-based visual features in order to reduce the inconsistency between the subjective user's similarity interpretation and the retrieval results produced by objective similarity models. A novel multi-scale segmentation framework is proposed to detect prominent image objects. These objects are clustered according to their visual features and mapped to related words determined by psychophysical studies. Furthermore, a hierarchy of words expressing higher-level meaning is determined on the basis of natural language processing and user evaluation. Experiments conducted on a large set of natural images showed that higher retrieval precision in terms of estimating user retrieval semantics could be achieved via this two-layer word association and also by supporting various query specifications and options.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125025238","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234035
Javier Ruiz-del-Solar, Alon Shats, Rodrigo Verschae
Robust tracking of persons in real-world environments and in real-time is a common goal in many video applications. In this paper a computational system for the real-time tracking of multiple persons in natural environments is presented. The system integrates state-of-the-art methodologies for the analysis of movement and color, as well as for the detection of faces. Face detection is complemented by a face tracking module based on heuristics developed by the authors. Exemplary results of the integrated system working in real-world video sequences are shown.
{"title":"Real-time tracking of multiple persons","authors":"Javier Ruiz-del-Solar, Alon Shats, Rodrigo Verschae","doi":"10.1109/ICIAP.2003.1234035","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234035","url":null,"abstract":"Robust tracking of persons in real-world environments and in real-time is a common goal in many video applications. In this paper a computational system for the real-time tracking of multiple persons in natural environments is presented. The system integrates state-of-the-art methodologies for the analysis of movement and color, as well as for the detection of faces. Face detection is complemented by a face tracking module based on heuristics developed by the authors. Exemplary results of the integrated system working in real-world video sequences are shown.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121212569","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234058
W. Pamuła
The properties of computing wavelet transforms of road traffic image data are discussed. It is proposed to incorporate a Hilbert scan of image data and a wavelet transform factorised into lifting steps. Scanning an image, in space filling curve order, brings together pixels that are highly correlated. This is a desirable property, because the objects of interest - vehicles - comprise a bounded set of regular patches on an image. Applying a 1-dimensional wavelet transform requires a smaller number of processing steps than a separable two-dimensional transform. Such a solution is suitable for on site microcontroller or FPGA implementation.
{"title":"Advantages of using a space filling curve for computing wavelet transforms of road traffic images","authors":"W. Pamuła","doi":"10.1109/ICIAP.2003.1234058","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234058","url":null,"abstract":"The properties of computing wavelet transforms of road traffic image data are discussed. It is proposed to incorporate a Hilbert scan of image data and a wavelet transform factorised into lifting steps. Scanning an image, in space filling curve order, brings together pixels that are highly correlated. This is a desirable property, because the objects of interest - vehicles - comprise a bounded set of regular patches on an image. Applying a 1-dimensional wavelet transform requires a smaller number of processing steps than a separable two-dimensional transform. Such a solution is suitable for on site microcontroller or FPGA implementation.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130995988","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234090
N. Gheissari, A. Bab-Hadiashar
A new model selection criterion based on physical characteristics of underlying motion models is proposed. The proposed criterion is then incorporated in a robust motion segmentation scheme, which is based upon robust least K-th order statistical model fitting. The proposed model criterion has been compared with many other competing techniques and is shown to be more suitable for the motion segmentation task. The motion segmentation algorithm has been tested (and shown to be successful) on a number of synthetic and real image sequences.
{"title":"Motion analysis: model selection and motion segmentation","authors":"N. Gheissari, A. Bab-Hadiashar","doi":"10.1109/ICIAP.2003.1234090","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234090","url":null,"abstract":"A new model selection criterion based on physical characteristics of underlying motion models is proposed. The proposed criterion is then incorporated in a robust motion segmentation scheme, which is based upon robust least K-th order statistical model fitting. The proposed model criterion has been compared with many other competing techniques and is shown to be more suitable for the motion segmentation task. The motion segmentation algorithm has been tested (and shown to be successful) on a number of synthetic and real image sequences.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128450602","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234028
D. Weiner, N. Kiryati
In video-conferencing, the participant watches the screen rather than the camera. This turns the gaze direction away from the other party and makes eye contact impossible. Artificial gaze redirection by iris repositioning has been proposed, but the feasibility of crucial algorithmic components, especially the challenging computer vision parts, was not demonstrated. This paper demonstrates a system for gaze redirection in color face images via eye synthesis and replacement. The proposed method can serve as an image editing tool for entertainment and commercial use, and is an important step towards gaze-redirection in video-conferencing.
{"title":"Virtual gaze redirection in face images","authors":"D. Weiner, N. Kiryati","doi":"10.1109/ICIAP.2003.1234028","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234028","url":null,"abstract":"In video-conferencing, the participant watches the screen rather than the camera. This turns the gaze direction away from the other party and makes eye contact impossible. Artificial gaze redirection by iris repositioning has been proposed, but the feasibility of crucial algorithmic components, especially the challenging computer vision parts, was not demonstrated. This paper demonstrates a system for gaze redirection in color face images via eye synthesis and replacement. The proposed method can serve as an image editing tool for entertainment and commercial use, and is an important step towards gaze-redirection in video-conferencing.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131760676","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}
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