Scale-Space and Morphology in Computer Vision, 2001
ABSTRACT We have been witnessing lately a convergence among mathematical morphology and other non... more ABSTRACT We have been witnessing lately a convergence among mathematical morphology and other nonlinear fields, such as curve evolution, PDE-based geometrical image processing, and scale-spaces. An obvious benefit of such a convergence is a cross-fertilization of concepts and techniques among these fields. The concept of adjunction however, so fundamental in mathematical morphology, is not yet shared by other disciplines. The aim of this paper is to show that other areas in image processing can possibly benefit from the use of adjunctions. In particular, it will be explained that adjunctions based on a curve evolution scheme can provide idempotent shape filters. This idea is illustrated in this paper by means of a simple affine-invariant polygonal flow.
| In recent years, the Morphological Skeleton Decomposition of images had its framework extended,... more | In recent years, the Morphological Skeleton Decomposition of images had its framework extended, leading to a Generalized Skeleton Decomposition. This work shows how the Quadtree Decomposition of binary images and the Bit-Plane decomposition of Grayscale pictures can both be seen as particular cases of such a generalized Skeleton.
We present a new tree-based framework for producing self-dual morphological operators. For any gi... more We present a new tree-based framework for producing self-dual morphological operators. For any given tree representation of im-ages, one can associate a complete inf-semilattice (CISL) in the corresponding tree-representation domain, where the operators can then be derived. We also present a particular case of this gen-eral framework, involving a new tree representation, the Extrema-Watershed Tree (EWT). The operators obtained by using the EWT in the above framework behave like classical morphological opera-tors, but in addition are self-dual. Some application examples are provided: pre-processing for OCR and dust & scratch removal al-gorithms, and image denoising.
In this paper we propose a new classifier - the Maximal Rejection Classifier (MRC) - for target d... more In this paper we propose a new classifier - the Maximal Rejection Classifier (MRC) - for target detection. Unlike pattern recognition, pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller, compared to that of the latter. The MRC is a linear classifier, based on successive rejection operations. Each rejection is performed using a projection followed by thresholding. The projection vector is designed to maximize the number of rejected Clutter inputs. It is shown that it also minimizes the expected number of operations until detection.
International Journal of Computer Vision - IJCV, 2003
We have been witnessing lately a convergence among mathematical morphology and other nonlinear fi... more We have been witnessing lately a convergence among mathematical morphology and other nonlinear fields, such as curve evolution, PDE-based geometrical image processing, and scale-spaces. An obvious benefit of such a convergence is a cross-fertilization of concepts and techniques among these fields. The concept of adjunction however, so fundamental in mathematical morphology, is not yet shared by other disciplines. The aim of this paper is to show that other areas in image processing can possibly benefit from the use of adjunctions. In particular, a strong relationship between pyramids and adjunctions is presented. We show how this relationship may help in analyzing existing pyramids, and construct new pyramids. Moreover, it will be explained that adjunctions based on a curve evolution scheme can provide idempotent shape filters. This idea is illustrated in this paper by means of a simple affine-invariant polygonal flow. Finally, the use of adjunctions in scale-space theory is also ad...
this paper. In most Retinex-type algorithms the computational engine is some (possibly non- linea... more this paper. In most Retinex-type algorithms the computational engine is some (possibly non- linear) variant of a large support low-pass filter. The presented work relies on the fact that recursive (2D IIR) filtering is an efficient method to implement such large support linear space invariant filters. We propose a generalization of recursive filters to non- liner operators, and their use in the Retinex core
Retinex theory addresses the problem of separating the illumination from the reflectance in a giv... more Retinex theory addresses the problem of separating the illumination from the reflectance in a given image, and thereby compensating for non-uniform lighting. In a previous paper , a variational model for the Retinex problem was introduced. This model was shown to unify previous methods, leading to a new illumination estimation algorithm. The main drawback with the above approach is its numerical implementation. The computational complexity of the illumination reconstruction algorithm is relatively high, since in the obtained Quadratic Programming (QP) problem, the whole image is the unknown. In addition, the process requirements for obtaining the optimal solution are not chosen a priori based on hardware/ software constraints. In this paper we propose a way to compromise between the full fledged solution of the theoretical model, and a variety of efficient yet limited computational methods for which we develop optimal solutions. For computational methods parameterized linearly by a small set of free parameters, it is shown that a reduced size QP problem is obtained with a unique solution. Several special cases of this general solution are presented and analyzed: a Look-Up-Table (LUT), linear or nonlinear Volterra filters, and expansion using a truncated set of basis functions. The proposed solutions are sub-optimal compared to the original Retinex algorithm, yet their numerical implementations are much more efficient. Results indicate that the proposed methodology can enhance images for a reduced computational effort.
Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2000
Classical morphology is built up in such a way that all op- erators occur in pairs, e.g., dilatio... more Classical morphology is built up in such a way that all op- erators occur in pairs, e.g., dilation and erosion, opening and closing, etc. This phenomenon, which is a straightfor- ward consequence of the duality principle, often prohibits the construction of tools that treat foreground and back- ground of signals in exactly the same way. In this paper we discuss
In this paper we propose a new classifier -the Maximal Rejection Classifier (MRC) -for target det... more In this paper we propose a new classifier -the Maximal Rejection Classifier (MRC) -for target detection. Unlike pattern recognition, pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller, compared to that of the latter. The MRC is a linear classifier, based on successive rejection operations. Each rejection is performed using a projection followed by thresholding. The projection vector is designed to maximize the number of rejected Clutter inputs. It is shown that it also minimizes the expected number of operations until detection. An application of detecting frontal faces in images is demonstrated using the MRC with encouraging results. This work has been done at HP Labs, Israel.
2010 IEEE International Conference on Image Processing, 2010
Estimating human pose in static images is challenging due to the high dimensional state space, pr... more Estimating human pose in static images is challenging due to the high dimensional state space, presence of image clutter and ambiguities of image observations. In this paper we propose a method to automatically segment human subjects in images, based on dominant colors, and given the face captured by a face detector. The posture is estimated using a 2D model combined with anthropometric data. Experimental results showed that the proposed technique performs well in non trivial images.
Pattern detection problems require a separation between two classes, Target and Clutter, where th... more Pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller compared to that of the latter. In this paper we propose a new classifier that exploits this property, yielding a low complexity yet effective target detection algorithm. This algorithm, called the maximal rejection classifier (MRC), is based on linear
2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009
This paper presents a novel self-similarity based approach for the problem of vanishing point est... more This paper presents a novel self-similarity based approach for the problem of vanishing point estimation in man-made scenes. A vanishing point (VP) is the convergence point of a pencil (a concurrent line set), that is a perspective projection of a corresponding parallel line set in the scene. Unlike traditional VP detection that relies on extraction and grouping of individual straight lines, our approach detects entire pencils based on a property of 1D affine-similarity between parallel cross-sections of a pencil. Our approach is not limited to real pencils. Under some conditions (normally met in man-made scenes), our method can detect pencils made of virtual lines passing through similar image features, and hence can detect VPs from repeating patterns that do not contain straight edges. We demonstrate that detecting entire pencils rather than individual lines improves the detection robustness in that it improves VP detection in challenging conditions, such as very-low resolution or weak edges, and simultaneously reduces VP false-detection rate when only a small number of lines are detectable.
International Symposium on Technologies for Digital Photo Fulfillment, 2009
a) (b) Figure 1. Image enhancement by the HP Smartstream Photo Enhancement Server. (a) Original i... more a) (b) Figure 1. Image enhancement by the HP Smartstream Photo Enhancement Server. (a) Original image, (b) after processing.
In this work we propose a further generalization of the Morphological Skeleton Decomposition on B... more In this work we propose a further generalization of the Morphological Skeleton Decomposition on Boolean Lattices. In this generalization, the family of structuring-functions which determines the decomposition has its scalar index replaced by a generic index i from a totally or partially ordered set I. This enables, for example, skeleton decompositions by richer and more complex families of shapes, characterized by several scalar indices (i.e., a multi-dimensional index), instead of just a single scalar index.
Journal of Visual Communication and Image Representation, 2003
Retinex theory addresses the problem of separating the illumination from the reflectance in a giv... more Retinex theory addresses the problem of separating the illumination from the reflectance in a given image, and thereby compensating for non-uniform lighting. In a previous paper , a variational model for the Retinex problem was introduced. This model was shown to unify previous methods, leading to a new illumination estimation algorithm. The main drawback with the above approach is its numerical implementation. The computational complexity of the illumination reconstruction algorithm is relatively high, since in the obtained Quadratic Programming (QP) problem, the whole image is the unknown. In addition, the process requirements for obtaining the optimal solution are not chosen a priori based on hardware/ software constraints. In this paper we propose a way to compromise between the full fledged solution of the theoretical model, and a variety of efficient yet limited computational methods for which we develop optimal solutions. For computational methods parameterized linearly by a small set of free parameters, it is shown that a reduced size QP problem is obtained with a unique solution. Several special cases of this general solution are presented and analyzed: a Look-Up-Table (LUT), linear or nonlinear Volterra filters, and expansion using a truncated set of basis functions. The proposed solutions are sub-optimal compared to the original Retinex algorithm, yet their numerical implementations are much more efficient. Results indicate that the proposed methodology can enhance images for a reduced computational effort.
Scale-Space and Morphology in Computer Vision, 2001
ABSTRACT We have been witnessing lately a convergence among mathematical morphology and other non... more ABSTRACT We have been witnessing lately a convergence among mathematical morphology and other nonlinear fields, such as curve evolution, PDE-based geometrical image processing, and scale-spaces. An obvious benefit of such a convergence is a cross-fertilization of concepts and techniques among these fields. The concept of adjunction however, so fundamental in mathematical morphology, is not yet shared by other disciplines. The aim of this paper is to show that other areas in image processing can possibly benefit from the use of adjunctions. In particular, it will be explained that adjunctions based on a curve evolution scheme can provide idempotent shape filters. This idea is illustrated in this paper by means of a simple affine-invariant polygonal flow.
| In recent years, the Morphological Skeleton Decomposition of images had its framework extended,... more | In recent years, the Morphological Skeleton Decomposition of images had its framework extended, leading to a Generalized Skeleton Decomposition. This work shows how the Quadtree Decomposition of binary images and the Bit-Plane decomposition of Grayscale pictures can both be seen as particular cases of such a generalized Skeleton.
We present a new tree-based framework for producing self-dual morphological operators. For any gi... more We present a new tree-based framework for producing self-dual morphological operators. For any given tree representation of im-ages, one can associate a complete inf-semilattice (CISL) in the corresponding tree-representation domain, where the operators can then be derived. We also present a particular case of this gen-eral framework, involving a new tree representation, the Extrema-Watershed Tree (EWT). The operators obtained by using the EWT in the above framework behave like classical morphological opera-tors, but in addition are self-dual. Some application examples are provided: pre-processing for OCR and dust & scratch removal al-gorithms, and image denoising.
In this paper we propose a new classifier - the Maximal Rejection Classifier (MRC) - for target d... more In this paper we propose a new classifier - the Maximal Rejection Classifier (MRC) - for target detection. Unlike pattern recognition, pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller, compared to that of the latter. The MRC is a linear classifier, based on successive rejection operations. Each rejection is performed using a projection followed by thresholding. The projection vector is designed to maximize the number of rejected Clutter inputs. It is shown that it also minimizes the expected number of operations until detection.
International Journal of Computer Vision - IJCV, 2003
We have been witnessing lately a convergence among mathematical morphology and other nonlinear fi... more We have been witnessing lately a convergence among mathematical morphology and other nonlinear fields, such as curve evolution, PDE-based geometrical image processing, and scale-spaces. An obvious benefit of such a convergence is a cross-fertilization of concepts and techniques among these fields. The concept of adjunction however, so fundamental in mathematical morphology, is not yet shared by other disciplines. The aim of this paper is to show that other areas in image processing can possibly benefit from the use of adjunctions. In particular, a strong relationship between pyramids and adjunctions is presented. We show how this relationship may help in analyzing existing pyramids, and construct new pyramids. Moreover, it will be explained that adjunctions based on a curve evolution scheme can provide idempotent shape filters. This idea is illustrated in this paper by means of a simple affine-invariant polygonal flow. Finally, the use of adjunctions in scale-space theory is also ad...
this paper. In most Retinex-type algorithms the computational engine is some (possibly non- linea... more this paper. In most Retinex-type algorithms the computational engine is some (possibly non- linear) variant of a large support low-pass filter. The presented work relies on the fact that recursive (2D IIR) filtering is an efficient method to implement such large support linear space invariant filters. We propose a generalization of recursive filters to non- liner operators, and their use in the Retinex core
Retinex theory addresses the problem of separating the illumination from the reflectance in a giv... more Retinex theory addresses the problem of separating the illumination from the reflectance in a given image, and thereby compensating for non-uniform lighting. In a previous paper , a variational model for the Retinex problem was introduced. This model was shown to unify previous methods, leading to a new illumination estimation algorithm. The main drawback with the above approach is its numerical implementation. The computational complexity of the illumination reconstruction algorithm is relatively high, since in the obtained Quadratic Programming (QP) problem, the whole image is the unknown. In addition, the process requirements for obtaining the optimal solution are not chosen a priori based on hardware/ software constraints. In this paper we propose a way to compromise between the full fledged solution of the theoretical model, and a variety of efficient yet limited computational methods for which we develop optimal solutions. For computational methods parameterized linearly by a small set of free parameters, it is shown that a reduced size QP problem is obtained with a unique solution. Several special cases of this general solution are presented and analyzed: a Look-Up-Table (LUT), linear or nonlinear Volterra filters, and expansion using a truncated set of basis functions. The proposed solutions are sub-optimal compared to the original Retinex algorithm, yet their numerical implementations are much more efficient. Results indicate that the proposed methodology can enhance images for a reduced computational effort.
Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2000
Classical morphology is built up in such a way that all op- erators occur in pairs, e.g., dilatio... more Classical morphology is built up in such a way that all op- erators occur in pairs, e.g., dilation and erosion, opening and closing, etc. This phenomenon, which is a straightfor- ward consequence of the duality principle, often prohibits the construction of tools that treat foreground and back- ground of signals in exactly the same way. In this paper we discuss
In this paper we propose a new classifier -the Maximal Rejection Classifier (MRC) -for target det... more In this paper we propose a new classifier -the Maximal Rejection Classifier (MRC) -for target detection. Unlike pattern recognition, pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller, compared to that of the latter. The MRC is a linear classifier, based on successive rejection operations. Each rejection is performed using a projection followed by thresholding. The projection vector is designed to maximize the number of rejected Clutter inputs. It is shown that it also minimizes the expected number of operations until detection. An application of detecting frontal faces in images is demonstrated using the MRC with encouraging results. This work has been done at HP Labs, Israel.
2010 IEEE International Conference on Image Processing, 2010
Estimating human pose in static images is challenging due to the high dimensional state space, pr... more Estimating human pose in static images is challenging due to the high dimensional state space, presence of image clutter and ambiguities of image observations. In this paper we propose a method to automatically segment human subjects in images, based on dominant colors, and given the face captured by a face detector. The posture is estimated using a 2D model combined with anthropometric data. Experimental results showed that the proposed technique performs well in non trivial images.
Pattern detection problems require a separation between two classes, Target and Clutter, where th... more Pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller compared to that of the latter. In this paper we propose a new classifier that exploits this property, yielding a low complexity yet effective target detection algorithm. This algorithm, called the maximal rejection classifier (MRC), is based on linear
2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009
This paper presents a novel self-similarity based approach for the problem of vanishing point est... more This paper presents a novel self-similarity based approach for the problem of vanishing point estimation in man-made scenes. A vanishing point (VP) is the convergence point of a pencil (a concurrent line set), that is a perspective projection of a corresponding parallel line set in the scene. Unlike traditional VP detection that relies on extraction and grouping of individual straight lines, our approach detects entire pencils based on a property of 1D affine-similarity between parallel cross-sections of a pencil. Our approach is not limited to real pencils. Under some conditions (normally met in man-made scenes), our method can detect pencils made of virtual lines passing through similar image features, and hence can detect VPs from repeating patterns that do not contain straight edges. We demonstrate that detecting entire pencils rather than individual lines improves the detection robustness in that it improves VP detection in challenging conditions, such as very-low resolution or weak edges, and simultaneously reduces VP false-detection rate when only a small number of lines are detectable.
International Symposium on Technologies for Digital Photo Fulfillment, 2009
a) (b) Figure 1. Image enhancement by the HP Smartstream Photo Enhancement Server. (a) Original i... more a) (b) Figure 1. Image enhancement by the HP Smartstream Photo Enhancement Server. (a) Original image, (b) after processing.
In this work we propose a further generalization of the Morphological Skeleton Decomposition on B... more In this work we propose a further generalization of the Morphological Skeleton Decomposition on Boolean Lattices. In this generalization, the family of structuring-functions which determines the decomposition has its scalar index replaced by a generic index i from a totally or partially ordered set I. This enables, for example, skeleton decompositions by richer and more complex families of shapes, characterized by several scalar indices (i.e., a multi-dimensional index), instead of just a single scalar index.
Journal of Visual Communication and Image Representation, 2003
Retinex theory addresses the problem of separating the illumination from the reflectance in a giv... more Retinex theory addresses the problem of separating the illumination from the reflectance in a given image, and thereby compensating for non-uniform lighting. In a previous paper , a variational model for the Retinex problem was introduced. This model was shown to unify previous methods, leading to a new illumination estimation algorithm. The main drawback with the above approach is its numerical implementation. The computational complexity of the illumination reconstruction algorithm is relatively high, since in the obtained Quadratic Programming (QP) problem, the whole image is the unknown. In addition, the process requirements for obtaining the optimal solution are not chosen a priori based on hardware/ software constraints. In this paper we propose a way to compromise between the full fledged solution of the theoretical model, and a variety of efficient yet limited computational methods for which we develop optimal solutions. For computational methods parameterized linearly by a small set of free parameters, it is shown that a reduced size QP problem is obtained with a unique solution. Several special cases of this general solution are presented and analyzed: a Look-Up-Table (LUT), linear or nonlinear Volterra filters, and expansion using a truncated set of basis functions. The proposed solutions are sub-optimal compared to the original Retinex algorithm, yet their numerical implementations are much more efficient. Results indicate that the proposed methodology can enhance images for a reduced computational effort.
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Papers by Renato Keshet