An Adaptive Harris Corner Detection Algorithm for Image Mosaic

2014 ◽  
pp. 53-62 ◽  
Author(s):  
Haixia Pan ◽  
Yanxiang Zhang ◽  
Chunlong Li ◽  
Huafeng Wang
Keyword(s):  
Detection Algorithm ◽  
Corner Detection ◽  
Image Mosaic ◽  
Harris Corner ◽  
Harris Corner Detection

An Improved Harris Corner Detection Algorithm for Noised Images

2012 ◽  
Vol 433-440 ◽  
pp. 6151-6156 ◽  
Author(s):  
Xin Zhang ◽  
Xiu Hua Ji
Keyword(s):  
Image Registration ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Corner Detection ◽  
Detection Accuracy ◽  
Image Mosaic ◽  
Harris Corner ◽  
Noise Impact ◽  
Corner Points ◽  
Harris Corner Detection

The Harris corner detection algorithm is widely applied in image mosaic, which is simple and stable. However, the algorithm has a disadvantage that it obtains a lot of false corners when there exist some noise in an image. An improved Harris corner detection algorithm is proposed in this paper. The new algorithm reduces the noise impact greatly. The experimental results show that the improved algorithm not only reduces false corner points greatly, but also retain the majority of true corners. As a result, it improves the detection accuracy and reduces the chance of error matching in image registration.

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.

scholarly journals Image Mosaic Method Based on SIFT Features of Line Segment

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Jun Zhu ◽  
Mingwu Ren
Keyword(s):  
Line Segment ◽  
Corner Detection ◽  
Image Mosaic ◽  
Scale Invariant ◽  
Point Matching ◽  
Lighting Condition ◽  
Harris Corner ◽  
Key Points ◽  
Scale Invariant Feature ◽  
Harris Corner Detection

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

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