Abstract. Digital image databases are becoming more widely used due to the rapid advances in imag... more Abstract. Digital image databases are becoming more widely used due to the rapid advances in image acquisition and storage mechanisms. The past years have evidenced therefore a rapid growth of such databases. In this sense, by considering not only their popularity, but also their large size, there exists an imminent need to provide users efficient and effective techniques to manage and interact with those collections in real-time.
Learning how to extract texture features from noncontrolled environments characterized by distort... more Learning how to extract texture features from noncontrolled environments characterized by distorted images is a still-open task. By using a new rotation-invariant and scale-invariant image descriptor based on steerable pyramid decomposition, and a novel multiclass recognition method based on optimum-path forest, a new texture recognition system is proposed. By combining the discriminating power of our image descriptor and classifier, our system uses small-size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz data set. High classification rates demonstrate the superiority of the proposed system.
By calculating the mean and standard deviation of decomposed image subbands, the texture feature ... more By calculating the mean and standard deviation of decomposed image subbands, the texture feature vectors are extracted. To obtain rotation or scale invariance, the feature elements are aligned by considering either the dominant orientation or dominant scale of the input textures.
Abstract This paper presents an unified framework for fast interactive segmentation of natural im... more Abstract This paper presents an unified framework for fast interactive segmentation of natural images using the image foresting transform (IFT)-a tool for the design of image processing operators based on connectivity functions (path-value functions) in graphs derived from the image. It mainly consists of three tasks: recognition, enhancement, and extraction. Recognition is the only interactive task, where representative image properties for enhancement and the object's location for extraction are indicated by drawing a few ...
This paper proposes a new texture classification system, which is distinguished by: (1) a new rot... more This paper proposes a new texture classification system, which is distinguished by: (1) a new rotation-invariant image descriptor based on Steerable Pyramid Decomposition, and (2) by a novel multi-class recognition method based on Optimum Path Forest. By combining the discriminating power of our image descriptor and classifier, our system uses small size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz dataset. High classification rates demonstrate the superiority of the proposed method.
Abstract This paper proposes a new texture descriptor to guide the search and retrieval in image ... more Abstract This paper proposes a new texture descriptor to guide the search and retrieval in image databases. It extracts rich information from global and local primitives of textured images. At a higher level, the global macro-features in textured images are characterized by exploiting the multiresolution properties of the Steerable Pyramid Decomposition. By doing this, the global texture configurations are highlighted. At a finer level, the local arrangements of texture micro-patterns are encoded by the Local Binary Pattern operator. Experiments ...
Edition of natural images usually asks for considerable user involvement, being segmentation one ... more Edition of natural images usually asks for considerable user involvement, being segmentation one of the main challenges. This paper describes an unified graph-based framework for fast, precise and accurate interactive image segmentation. The method divides segmentation into object recognition, enhancement and extraction. Recognition is done by the user when markers are selected inside and outside the object. Enhancement increases the dissimilarities between object and background and Extraction separates them. Enhancement is done by a fuzzy pixel classifier and it has a great impact in the number of markers required for extraction. In view of minimizing user involvement, we focus this paper on a comparative study among popular classifiers for enhancement, conducting experiments with several natural images and seven users.
This paper proposes novel exclusive and continuous approaches to guide the search and the retriev... more This paper proposes novel exclusive and continuous approaches to guide the search and the retrieval in fingerprint image databases. Both approaches are useful to perform a coarse level classification of fingerprint images before fingerprint authentication tasks. Our approaches are characterized by:(1) texture image descriptors based on pairs of multi-resolution decomposition methods that encode effectively global and local fingerprint information, with similarity measures used for fingerprint matching purposes, and (2) a ...
This paper presents a novel approach for personal identification based on a waveletbased fingerpr... more This paper presents a novel approach for personal identification based on a waveletbased fingerprint retrieval system which encompasses three image retrieval tasks, namely, feature extraction, similarity measurement, and feature indexing.
Abstract. The image foresting transform (IFT) can divide an image into object and background, eac... more Abstract. The image foresting transform (IFT) can divide an image into object and background, each represented by one optimum-path forest rooted at internal and external markers selected by the user. We have considerably reduced the number of markers (user involvement) by separating object enhancement from its extraction. However, the user had no guidance about effective marker location during extraction, losing segmentation control. Now, we pre-segment the image automatically into a few regions. The regions inside the ...
Abstract. Digital image databases are becoming more widely used due to the rapid advances in imag... more Abstract. Digital image databases are becoming more widely used due to the rapid advances in image acquisition and storage mechanisms. The past years have evidenced therefore a rapid growth of such databases. In this sense, by considering not only their popularity, but also their large size, there exists an imminent need to provide users efficient and effective techniques to manage and interact with those collections in real-time.
Learning how to extract texture features from noncontrolled environments characterized by distort... more Learning how to extract texture features from noncontrolled environments characterized by distorted images is a still-open task. By using a new rotation-invariant and scale-invariant image descriptor based on steerable pyramid decomposition, and a novel multiclass recognition method based on optimum-path forest, a new texture recognition system is proposed. By combining the discriminating power of our image descriptor and classifier, our system uses small-size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz data set. High classification rates demonstrate the superiority of the proposed system.
By calculating the mean and standard deviation of decomposed image subbands, the texture feature ... more By calculating the mean and standard deviation of decomposed image subbands, the texture feature vectors are extracted. To obtain rotation or scale invariance, the feature elements are aligned by considering either the dominant orientation or dominant scale of the input textures.
Abstract This paper presents an unified framework for fast interactive segmentation of natural im... more Abstract This paper presents an unified framework for fast interactive segmentation of natural images using the image foresting transform (IFT)-a tool for the design of image processing operators based on connectivity functions (path-value functions) in graphs derived from the image. It mainly consists of three tasks: recognition, enhancement, and extraction. Recognition is the only interactive task, where representative image properties for enhancement and the object's location for extraction are indicated by drawing a few ...
This paper proposes a new texture classification system, which is distinguished by: (1) a new rot... more This paper proposes a new texture classification system, which is distinguished by: (1) a new rotation-invariant image descriptor based on Steerable Pyramid Decomposition, and (2) by a novel multi-class recognition method based on Optimum Path Forest. By combining the discriminating power of our image descriptor and classifier, our system uses small size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz dataset. High classification rates demonstrate the superiority of the proposed method.
Abstract This paper proposes a new texture descriptor to guide the search and retrieval in image ... more Abstract This paper proposes a new texture descriptor to guide the search and retrieval in image databases. It extracts rich information from global and local primitives of textured images. At a higher level, the global macro-features in textured images are characterized by exploiting the multiresolution properties of the Steerable Pyramid Decomposition. By doing this, the global texture configurations are highlighted. At a finer level, the local arrangements of texture micro-patterns are encoded by the Local Binary Pattern operator. Experiments ...
Edition of natural images usually asks for considerable user involvement, being segmentation one ... more Edition of natural images usually asks for considerable user involvement, being segmentation one of the main challenges. This paper describes an unified graph-based framework for fast, precise and accurate interactive image segmentation. The method divides segmentation into object recognition, enhancement and extraction. Recognition is done by the user when markers are selected inside and outside the object. Enhancement increases the dissimilarities between object and background and Extraction separates them. Enhancement is done by a fuzzy pixel classifier and it has a great impact in the number of markers required for extraction. In view of minimizing user involvement, we focus this paper on a comparative study among popular classifiers for enhancement, conducting experiments with several natural images and seven users.
This paper proposes novel exclusive and continuous approaches to guide the search and the retriev... more This paper proposes novel exclusive and continuous approaches to guide the search and the retrieval in fingerprint image databases. Both approaches are useful to perform a coarse level classification of fingerprint images before fingerprint authentication tasks. Our approaches are characterized by:(1) texture image descriptors based on pairs of multi-resolution decomposition methods that encode effectively global and local fingerprint information, with similarity measures used for fingerprint matching purposes, and (2) a ...
This paper presents a novel approach for personal identification based on a waveletbased fingerpr... more This paper presents a novel approach for personal identification based on a waveletbased fingerprint retrieval system which encompasses three image retrieval tasks, namely, feature extraction, similarity measurement, and feature indexing.
Abstract. The image foresting transform (IFT) can divide an image into object and background, eac... more Abstract. The image foresting transform (IFT) can divide an image into object and background, each represented by one optimum-path forest rooted at internal and external markers selected by the user. We have considerably reduced the number of markers (user involvement) by separating object enhancement from its extraction. However, the user had no guidance about effective marker location during extraction, losing segmentation control. Now, we pre-segment the image automatically into a few regions. The regions inside the ...
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Papers by Javier Montoya