A Fuzzy-Like Approach for Smoothing and Edge Detection in Color Images

1998 ◽  
Vol 12 (06) ◽  
pp. 801-816 ◽  
Author(s):  
A. Moghaddamzadeh ◽  
D. Goldman ◽  
N. Bourbakis
Keyword(s):  
Edge Detection ◽  
Image Understanding ◽  
Detection Algorithm ◽  
Color Images ◽  
Color Contrast ◽  
Edge Detection Algorithm ◽  
Edge Contrast ◽  
Hsi Space ◽  
Fuzzy Like ◽  
Processing Steps

Edge detection is one of the most important image processing steps towards image understanding. It is desired that edges be continuous and that the resultant regions or segments be completely isolated from their neighbors. Initially, images must first be smoothed to remove noise. In this paper, a novel fuzzy-like smoother algorithm is presented which removes camera noise and enhances edge contrast. The edge detection algorithm, which is applied on the smoothed image, is then presented. In this algorithm normalized hue in HSI space and color contrast in RGB space are combined using an aggregate operator. Pixels considered to be at least "nearly" locally maximum (defined within) are then found for all edge directions and the results are combined.

A Novel Approach of Edge Detection Based on Vector Morphology

2014 ◽  
Vol 511-512 ◽  
pp. 545-549
Author(s):  
Qiang Chen
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Color Image ◽  
Detection Algorithm ◽  
Difficult Problem ◽  
Color Images ◽  
Edge Detection Algorithm ◽  
Morphological Gradient ◽  
Novel Approach ◽  
Image Edges

Edge detection of color image is a difficult problem in image processing. Although a lot of corresponding to methods have been proposed, however, none of them can effectively detect image edges while suppressing noises. In this paper, a novel edge detection algorithm of color images based on mathematical morphology is proposed. Through designing a new anti-noise morphological gradient operators, we can obtain better edge detection results. The proposed gradient operators are applied to detect edge for three components of a color image. An then, the final edge can be obtained by fusing the three edge results. Experimental results show that the feasibility and effectiveness of the proposed algorithm. Moreover, the proposed algorithm has better effect of preserving the edge details and better robustness to noises than traditional methods.

scholarly journals Image Edge Detection Algorithm Based on Fuzzy Radial Basis Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lin Feng ◽  
Jian Wang ◽  
Chao Ding
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Image Understanding ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Median Filters ◽  
Detection Techniques ◽  
Image Edge Detection ◽  
Radial Basis ◽  
Image Edge

Digital image processing technology is widely used in production and life, and digital images play a pivotal role in the ever-changing technological development. Noise can affect the expression of image information. The edge is the reflection of the main structure and contour of the image, and it is also the direct interpretation of image understanding and the basis for further segmentation and recognition. Therefore, suppressing noise and improving the accuracy of edge detection are important aspects of image processing. To address these issues, this paper presents a new detection algorithm combined with information fusion based on the existing image edge detection techniques, and the algorithm is studied from two aspects of fuzzy radial basis fusion discrimination, in terms of preprocessing algorithm, comparing the denoising effect of mean and median filters with different template sizes on paper images with added noise, and selecting the improved median filter denoising, comparing different operator edge detection. The effect of image edge detection contour is finally selected as the 3 ∗ 3 Sobel operator for edge detection; the binarized image edge detection contour information is found as the minimum outer rectangle and labeled, and then, the original paper image is scanned line by line to segment the target image edge region. The image edge detection algorithm based on fuzzy radial basis fuser can not only speed up the image preprocessing, meet the real-time detection, and reduce the amount of data processed by the upper computer but also can accurately identify five image edge problems including folds and cracks, which has good application prospects.

scholarly journals Design of Vision based Edge Detection under Different Conditions

2019 ◽  
Vol 9 (1S) ◽  
pp. 86-90
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Real Time ◽  
Detection Algorithm ◽  
Zero Crossing ◽  
Edge Detection Algorithm ◽  
Matlab Simulink ◽  
Detection Techniques ◽  
Simulink Model ◽  
Processing Steps

This work gives a detailed account of putting into effect of a Sobel algorithm to detect an Edge. In this model the camera is put on the vehicle(car) by recorded the real time video. The video is taken by camera will go to the different image processing steps which includes Intensity image, changing size, Interested region and Edge detection algorithm used to detect edges. Edge detection techniques various mathematical tools which are used to making outpoints in an image at which the image contrast changes sharply.So many Edge detection algorithms used there such as search-based and zero-crossing based.. The most commonly search based algorithms used are Sobel and canny's edge detection algorithm. In this work of making observations we give out with MATLAB SIMULINK model for Sobel algorithm which are used to detect edge. In this work of making observations work as first started to make a constructive video using Prescan software and a real time video of Lane taken by camera in dissimilar light, weather and road conditions is processed by using image processing algorithms , and Edge detection to detect edges. In this work of making observations we give out with MATLAB SIMULINK design to be for image processing steps and Sobel edge detection algorithm.

Application of Improved Canny Edge Detection Algorithm in Coal-Rock Interface Recognition

2012 ◽  
Vol 220-223 ◽  
pp. 1279-1283 ◽  
Author(s):  
Li Hong Dong ◽  
Peng Bing Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Rock Interface ◽  
Coal Rock ◽  
Image Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adaptive median filtering algorithm to calculate the thresholds of Canny algorithm according to the grayscale mean and variance mean. This algorithm can protect the image edge details better and can restrain the blurred image edge. Experimental results show that this algorithm has improved the edge extraction effect under the case of noise interference and improved the detection precision and accuracy of the coal-rock image effectively.

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