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A Shearlet Approach to Edge Analysis and Detection
"... It is well known that the wavelet transform provides a very effective framework for analysis of multiscale edges. In this paper, we propose a novel approach based on the shearlet transform: a multiscale directional transform with a greater ability to localize distributed discontinuities such as edg ..."
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Cited by 57 (27 self)
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It is well known that the wavelet transform provides a very effective framework for analysis of multiscale edges. In this paper, we propose a novel approach based on the shearlet transform: a multiscale directional transform with a greater ability to localize distributed discontinuities such as edges. Indeed, unlike traditional wavelets, shearlets are theoretically optimal in representing images with edges and, in particular, have the ability to fully capture directional and other geometrical features. Numerical examples demonstrate that the shearlet approach is highly effective at detecting both the location and orientation of edges, and outperforms methods based on wavelets as well as other standard methods. Furthermore, the shearlet approach is useful to design simple and effective algorithms for the detection of corners and junctions.
From First Contact to Close Encounters: A Developmentally Deep Perceptual System for a Humanoid Robot
, 2003
"... This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain ..."
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Cited by 49 (8 self)
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This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, segmentation, and recognition, starting from very little. What the robot starts with is a direct solution to achieving figure/ground separation: it simply `pokes around' in a region of visual ambiguity and watches what happens. If the arm passes through an area, that area is recognized as free space. If the arm collides with an object, causing it to move, the robot can use that motion to segment the object from the background. Once the robot can acquire reliable segmented views of objects, it learns from them, and from then on recognizes and segments those objects without further contact. Both low-level and high-level visual features can also be learned in this way, and examples are presented for both: orientation detection and affordance recognition, respectively.
A Method for Objective Edge Detection Evaluation and Detector Parameter Selection
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2003
"... Subjective evaluation by human observers is usually used to analyze and select an edge detector parametric setup when real-world images are considered. In this paper, we propose a statistical objective performance analysis and detector parameter selection, using detection results produced by differe ..."
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Cited by 38 (1 self)
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Subjective evaluation by human observers is usually used to analyze and select an edge detector parametric setup when real-world images are considered. In this paper, we propose a statistical objective performance analysis and detector parameter selection, using detection results produced by different detector parameters. Using the correspondence between the different detection results, an estimated best edge map, utilized as an estimated ground truth (EGT), is obtained. This is done using both a receiver operating characteristics (ROC) analysis and a Chi-square test, and considers the trade off between information and noisiness in the detection results. The best edge detector parameter set (PS) is then selected by the same statistical approach, using the EGT. Results are demonstrated for several edge detection techniques, and compared to published subjective evaluation results. The method developed here suggests a general tool to assist in practical implementations of parametric edge detectors where an automatic process is required.
Characterization and analysis of edges using the continuous shearlet transform
"... Abstract. This paper shows that the continuous shearlet transform, a novel directional multiscale transform recently introduced by the authors and their collaborators, provides a precise geometrical characterization for the boundary curves of very general planar regions. This study is motivated by i ..."
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Cited by 34 (20 self)
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Abstract. This paper shows that the continuous shearlet transform, a novel directional multiscale transform recently introduced by the authors and their collaborators, provides a precise geometrical characterization for the boundary curves of very general planar regions. This study is motivated by imaging applications, where such boundary curves represent edges of images. The shearlet approach is able to characterize both locations and orientations of the edge points, including corner points and junctions, where the edge curves exhibit abrupt changes in tangent or curvature. Our results encompass and greatly extend previous results based on the shearlet and curvelet transforms which were limited to very special cases such as polygons and smooth boundary curves with nonvanishing curvature. Key words. Analysis of singularities, continuous wavelets, curvelets, directional wavelets, edge detection, shearlets, wavelets AMS subject classifications. 42C15, 42C40
Edge analysis and identification using the continuous shearlet transform
"... transform ..."
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Architectural Modeling from Sparsely Scanned Range Data ∗
, 2007
"... We present a pipeline to reconstruct complete geometry of architectural buildings from point clouds obtained by sparse range laser scanning. Due to limited accessibility of outdoor environments, complete and sufficient scanning of every face of an architectural building is often impossible. Our pipe ..."
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Cited by 22 (0 self)
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We present a pipeline to reconstruct complete geometry of architectural buildings from point clouds obtained by sparse range laser scanning. Due to limited accessibility of outdoor environments, complete and sufficient scanning of every face of an architectural building is often impossible. Our pipeline deals with architectures that are made of planar faces and faithfully constructs a polyhedron of low complexity based on the incomplete scans. The pipeline first recognizes planar regions based on point clouds, then proceeds to compute plane intersections and corners 1, and finally produces a complete polyhedron. Within the pipeline, several algorithms based on the polyhedron geometry assumption are designed to perform data clustering, boundary detection, and face extraction. Our system offers a convenient user interface but minimizes the necessity of user intervention. We demonstrate the capability and advantage of our system by modeling real-life buildings. Keywords 3D scanning; range image; geometry reconstruction 1
A fast and robust iris localization method based on texture segmentation
- for Biometric Authentication and Testing, National Laboratory of Pattern Recognition,Chinese Academy of Sciences
, 2004
"... With the development of the current networked society, personal identification based on biometrics has received more and more attention. Iris recognition has a satisfying performance due to its high reliability and non-invasion. In an iris recognition system, preprocessing, especially iris localizat ..."
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Cited by 21 (0 self)
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With the development of the current networked society, personal identification based on biometrics has received more and more attention. Iris recognition has a satisfying performance due to its high reliability and non-invasion. In an iris recognition system, preprocessing, especially iris localization plays a very important role. The speed and performance of an iris recognition system is crucial and it is limited by the results of iris localization to a great extent. Iris localization includes finding the iris boundaries (inner and outer) and the eyelids (lower and upper). In this paper, we propose an iris localization algorithm based on texture segmentation. First, we use the information of low frequency of wavelet transform of the iris image for pupil segmentation and localize the iris with a differential integral operator. Then the upper eyelid edge is detected after eyelash is segmented. Finally, the lower eyelid is localized using parabolic curve fitting based on gray value segmentation. Extensive experimental results show that the algorithm has satisfying performance and good robustness.
Automated Correction and Updating of Road Databases from High-Resolution Imagery
- Canadian Journal of Remote Sensing
, 1999
"... Our work addresses the correction and update of road map data from georeferenced aerial images. This task requires the solution of two underlying problems: a) the weak positional accuracy of the existing road location, and b) the detection of new roads. To correct the position of the existing road n ..."
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Cited by 21 (6 self)
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Our work addresses the correction and update of road map data from georeferenced aerial images. This task requires the solution of two underlying problems: a) the weak positional accuracy of the existing road location, and b) the detection of new roads. To correct the position of the existing road network location from the imagery, we use an active contour ("snakes") optimization approach, with a line enhancement function. The initialization of the snakes is based on a priori knowledge derived from the existing vector road data coming from the National Topographic Database of Geomatics Canada, and from line junctions computed from the image by a new detector developed for this application. To generate hypothesis for new roads, a road following algorithm is applied, starting from the line intersections, which are already in the existing road network. Experimental results are presented to validate the approach and to demonstrate the interest of using line junctions in this kind of applications.
Detecting region outliers in meteorological data,”
- in Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems,
, 2003
"... ABSTRACT Spatial outliers are the spatial objects with distinct features from their surrounding neighbors. Detection of spatial outliers helps reveal important and valuable information from large spatial data sets. In the field of meteorology, for example, spatial outliers can be associated with di ..."
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Cited by 12 (3 self)
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ABSTRACT Spatial outliers are the spatial objects with distinct features from their surrounding neighbors. Detection of spatial outliers helps reveal important and valuable information from large spatial data sets. In the field of meteorology, for example, spatial outliers can be associated with disastrous natural events such as tornadoes, hurricane, and forest fires. Previous study of spatial outlier mainly focuses on point data. However, in the meteorological data or other applications, spatial outliers are frequently represented in region, i.e., a group of points, with two dimensions or even three dimensions, and the previous point-based approaches may not be appropriate to be used. As region outliers are commonly multi-scale objects, wavelet analysis is an effective tool to study them. In this paper, we propose a wavelet analysis based approach to detect region outliers. We discuss the region outlier detection problem and design a suite of algorithms to effectively discover them. The algorithms were implemented and evaluated with a real-world meteorological data set.
Classification of Color Edges in Video into Shadow-Geometry, Highlight, or Material Transitions
- Highlight, or Material Transitions, IEEE Trans. on Multimedia
, 2003
"... We aim at using color information to classify the physical nature of a color edge. To achieve physics-based edge classification, we propose a taxonomy of color invariant edges. Further, we present a framework for automatic color edge detection and noise-adaptive thresholding derived from sensor n ..."
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Cited by 9 (3 self)
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We aim at using color information to classify the physical nature of a color edge. To achieve physics-based edge classification, we propose a taxonomy of color invariant edges. Further, we present a framework for automatic color edge detection and noise-adaptive thresholding derived from sensor noise analysis and propagation.
