Infrared image edge detection algorithm based on sobel and ant colony algorithm

Author(s):  
Dong Wang ◽  
Jingzhou Zhang
2012 ◽  
Vol 41 (11) ◽  
pp. 1354-1358 ◽  
Author(s):  
王巍 WANG Wei ◽  
安友伟 AN You-wei ◽  
黄展 HUANG Zhan ◽  
丁锋 DING Feng ◽  
杨铿 YANG Keng ◽  
...  

Author(s):  
Jingyu Zhang ◽  
Jianfu Teng ◽  
Yu Bai

Taking the improved ant colony algorithm based on bacterial chemotaxis as a means, this paper proposes one new swarm intelligence optimization algorithm to solve the medical image edge detection problem. The improved ant colony algorithm based on bacterial chemotaxis mainly aims at the shortcoming that the basic ant colony algorithm lacks initial pheromone, and combines bacterial chemotaxis algorithm with basic ant colony algorithm. Firstly, feasible better solution can be found through bacterial chemotaxis algorithm and fed back as initial pheromone. Then ant colony algorithm is implemented to search for the global optimal solution. The algorithm test indicates that the improved ant colony algorithm is more effective in the aspects of searching precision, reliability, optimization speed and stability compared with basic ant colony algorithm. Finally, the improved ant colony algorithm is applied into the edge detection of medical image. It can be seen from the computer simulation that compared with other operators and basic ant colony algorithm on the issue of solving medical image edge detection, the improved ant colony algorithm has superiority and the detected edge is clearer.


2013 ◽  
Vol 347-350 ◽  
pp. 3541-3545 ◽  
Author(s):  
Dan Dan Zhang ◽  
Shuang Zhao

The traditional Canny edge detection algorithm is analyzed in this paper. To overcome the difficulty of threshold selecting in Canny algorithm, an improved method based on Otsu algorithm and mathematical morphology is proposed to choose the threshold adaptively and simultaneously. This method applies the improved Canny operator and the image morphology separately to image edge detection, and then performs image fusion of the two results using the wavelet fusion technology to obtain the final edge-image. Simulation results show that the proposed algorithm has better anti-noise ability and effectively enhances the accuracy of image edge detection.


2020 ◽  
Vol 38 (4) ◽  
pp. 3557-3566
Author(s):  
Shuqiang Wang ◽  
Shuo Liang ◽  
Fei Peng

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3555-3557

Showing a genuine 3 dimensional (3D) objects with the striking profundity data is dependably a troublesome and cost-devouring procedure. Speaking to 3D scene without a noise (raw image) is another case. With a honed technique for survey profundity measurement can be effortlessly gotten, without requiring any extraordinary instrument. In this paper, we have proposed an edge recognition process in a profundity picture dependent on the picture based smoothing and morphological activities.In this strategy, we have utilized the guideline of Median sifting, which has a prestigious element for edge safeguarding properties. The edge discovery was done dependent on the Canny Edge Detection Algorithm. Along these lines this strategy will help to identify edges powerfully from profundity pictures and add to advance applications top to bottom pictures


2012 ◽  
Vol 214 ◽  
pp. 375-380 ◽  
Author(s):  
Tie Yun Li

An edge detection algorithm is developed for coal gangue images, and the method has two advantages compared with traditional ones. Firstly, multi-resolution analysis of wavelet transform can improve the quality of edge detection. Secondly, the algorithm is faster for real time. Since the threshold directly from the coefficients of wavelet transform, the rate of recognition for coal gangue is highly raised. The experiment results show that the method is an efficient edge detection algorithm for extraction edges from the noised images of coal gangues.


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