Adaptive Harris corner detection algorithm based on iterative threshold

2017 ◽  
Vol 31 (15) ◽  
pp. 1750181 ◽  
Author(s):  
Zhicheng Wang ◽  
Rong Li ◽  
Zhihao Shao ◽  
Mengxin Ma ◽  
Jianhui Liang ◽  
...  
Keyword(s):  
Threshold Value ◽  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Corner Detection ◽  
Threshold Selection ◽  
Harris Corner ◽  
Simulation Results ◽  
Threshold Setting ◽  
Harris Corner Detection ◽  
Iterative Threshold

An adaptive Harris corner detection algorithm based on the iterative threshold is proposed for the problem that the corner detection algorithm must be given a proper threshold when the corner detection algorithm is extracted. In order to avoid the phenomenon of clustering and restrain the pseudo corner, this algorithm realizes the adaptive threshold selection by iteration instead of the threshold value of the Harris corner detection algorithm. Simulation results show that the proposed method achieves good results in terms of threshold setting and feature extraction.

A WT-Based Edge Detection with Adaptive Threshold

2011 ◽  
Vol 204-210 ◽  
pp. 1386-1389
Author(s):  
Deng Yin Zhang ◽  
Li Xiao ◽  
Shun Rong Bo
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Value Iteration ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Image Edge ◽  
Threshold Setting

The existing edge detection algorithms with wavelet transform need to artificially set the threshold value and are lack of flexibility.To salve the limitations, in this paper, we propose a WT(wavelet transform)-based edge detection algorithm with adaptive threshold, which uses threshold value iteration method to achieve adaptive threshold setting. Comparison of experiment results for the CT image shows that the method which improve the clarity and continuity of the image edge can effectively distinguish edge and noise, and get more completely information of the edge. It has good application value in the fields of medical clinical diagnosis and image processing.

scholarly journals An Improved Corner Detection Algorithm Based on Harris

2012 ◽  
Vol 6-7 ◽  
pp. 717-721 ◽  
Author(s):  
Zhao Yang Zeng ◽  
Zhi Qiang Jiang ◽  
Qiang Chen ◽  
Pan Feng He
Keyword(s):  
Computation Time ◽  
Detection Algorithm ◽  
Corner Detection ◽  
Test Results ◽  
Harris Corner ◽  
Texture Complexity ◽  
Harris Corner Detection ◽  
Better Than

In order to accurately extract corners from the image with high texture complexity, the paper analyzed the traditional corner detection algorithm based on gray value of image. Although Harris corner detection algorithm has higher accuracy, but there also exists the following problems: extracting false corners, the information of the corners is missing and computation time is a bit long. So an improved corner detection algorithm combined Harris with SUSAN corner detection algorithm is proposed, the new algorithm first use the Harris to detect corners of image, then use the SUSAN to eliminate the false corners. By comparing the test results show that the new algorithm to extract corners very effective, and better than the Harris algorithm in the performance of corner detection.

Detection of honeycomb cell walls from measurement data based on Harris corner detection algorithm

2018 ◽  
Vol 29 (6) ◽  
pp. 065004
Author(s):  
Yan Qin ◽  
Zhigang Dong ◽  
Renke Kang ◽  
Jie Yang ◽  
Babajide O Ayinde
Keyword(s):  
Cell Walls ◽  
Measurement Data ◽  
Detection Algorithm ◽  
Corner Detection ◽  
Harris Corner ◽  
Honeycomb Cell ◽  
Harris Corner Detection
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