Journal ArticleDOI
Review article: Edge and line oriented contour detection: State of the art
Giuseppe Papari,Nicolai Petkov +1 more
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TLDR
The main conclusion is that contour detection has reached high degree of sophistication, taking into account multimodal contour definition (by luminance, color or texture changes), mechanisms for reducing the contour masking influence of noise and texture, perceptual grouping, multiscale aspects and high-level vision information.About:
This article is published in Image and Vision Computing.The article was published on 2011-02-01. It has received 347 citations till now. The article focuses on the topics: Phase congruency & Scale space.read more
Citations
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A survey of recent advances in visual feature detection
TL;DR: The recent progress in visual feature detection is presented and future trends as well as challenges are identified and the relations among different kinds of features are covered.
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Accurate subpixel edge location based on partial area effect
TL;DR: A new edge detector based on an edge and acquisition model derived from the partial area effect, which does not assume continuity in the image values is presented, achieving a highly accurate extraction of the position, orientation, curvature and contrast of the edges.
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Image-based mapping of surface fissures for the investigation of landslide dynamics
TL;DR: In this paper, a largely automated technique for the mapping of landslide surface fissures from very high-resolution aerial images was proposed, which includes the use of filtering algorithms and post-processing of the filtered images using object-oriented analysis.
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Improved spatial fuzzy c-means clustering for image segmentation using PSO initialization, Mahalanobis distance and post-segmentation correction
TL;DR: The proposed improvement method, named improved spatial fuzzy c-means IFCMS, was evaluated on several test images including both synthetic images and simulated brain MRI images from the McConnell Brain Imaging Center (BrainWeb) database and demonstrates the efficiency of the ideas presented.
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Quantitative error measures for edge detection
TL;DR: A comprehensive overview of the different proposals for edge detection performance measures is made, followed by a practical comparison of the most representative measures on synthetic as well as natural edge images.
References
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Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Book
Introduction to Algorithms
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.