Proceedings ArticleDOI
Fuzzy Edge and Corner Detector for Color Images
Hanmandlu Madasu,Om Prakash Verma,Pankaj Gangwar,Shantaram Vasikarla +3 more
- pp 1301-1306
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TLDR
An approach to edge and corner detection based on fuzzy logic is presented that is less sensitive to noise without causing edge displacement and an attempt is made to extend the proposed approach to the detection of colour edges.Abstract:
Localization of edges and corner points by fuzzy detectors in images is the main concern of this paper. This paper presents an approach to edge and corner detection based on fuzzy logic. In this approach SUSAN mask is employed to compute USAN area. The histogram of USAN area permits us construct type 1 and type 2 fuzzy membership functions by fuzzifying USAN area computed about every pixel in an image. The edge map of the image is obtained using adaptive thresholding. An attempt is made to extend the proposed approach to the detection of colour edges. Experiments show that this approach is less sensitive to noise without causing edge displacement.read more
Citations
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Journal ArticleDOI
An Optimal Fuzzy System for Edge Detection in Color Images Using Bacterial Foraging Algorithm
TL;DR: This paper presents a fuzzy system for edge detection, using smallest univalue segment assimilating nucleus (USAN) principle and bacterial foraging algorithm (BFA) and a parametric fuzzy intensification operator (FINT) to enhance the weak edge information, which results in another fuzzy set.
Journal ArticleDOI
Application of Type-2 Fuzzy Logic Filtering to Reduce Noise in Color Images
Mehmet Emin Yuksel,Alper Basturk +1 more
TL;DR: The results demonstrate that the type-2 fuzzy logic based impulse detector can be used as an efficient tool to effectively improve the performances of impulse noise filters and reduce the impulse noise undesirable distortion effects.
Journal ArticleDOI
Automatic segmentation of vertebral contours from CT images using fuzzy corners
TL;DR: The paper presents a methodology for automatic contour initialization in ACM and demonstrates the applicability of the method for medical image segmentation from spinal CT images and enables the ACM to efficiently converge to the ground truth segmentation.
Proceedings ArticleDOI
An optimal edge detection using universal law of gravity and ant colony algorithm
Om Prakash Verma,Rishabh Sharma +1 more
TL;DR: In the proposed approach the heuristic function is calculated using law of universal gravity which acts as the way to a food source for the artificial ants to detect the edge pixels.
Proceedings ArticleDOI
Newtonian Gravitational Edge Detection Using Gravitational Search Algorithm
Om Prakash Verma,Rishabh Sharma +1 more
TL;DR: The proposed approach is able to detect the edge pixel in an image up to a certain extent and can be further extended for finding more edge pixels by modifying the gravitational search algorithm.
References
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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.
Proceedings ArticleDOI
A Combined Corner and Edge Detector
Chris Harris,Mike Stephens +1 more
TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
Journal ArticleDOI
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TL;DR: This paper describes a new approach to low level image processing; in particular, edge and corner detection and structure preserving noise reduction and the resulting methods are accurate, noise resistant and fast.
Journal ArticleDOI
Feature Detection with Automatic Scale Selection
TL;DR: It is shown how the proposed methodology applies to the problems of blob detection, junction detection, edge detection, ridge detection and local frequency estimation and how it can be used as a major mechanism in algorithms for automatic scale selection, which adapt the local scales of processing to the local image structure.
Journal ArticleDOI
The Curvature Primal Sketch
Haruo Asada,J. Michael Brady +1 more
TL;DR: An implemented algorithm is described that computes the Curvature Primal Sketch by matching the multiscale convolutions of a shape, and its performance on a set of tool shapes is illustrated.