Fast communication: Analysis and improvement of SUSAN algorithm

Authors:
Chao Gao;Hongjun Zhu;Yongcai Guo
Affiliations:
Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400030, China;Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400030, China;Key Laboratory of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400030, China
Venue:
Signal Processing
Year:
2012

Citing 18
Cited 1

Extracting straight lines

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
On Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of digital image processing

Fundamentals of digital image processing
The use of Boolean functions and local operations for edge detection in images

Signal Processing
SUSAN—A New Approach to Low Level Image Processing

International Journal of Computer Vision
Computer Vision and Image Processing: A Practical Approach Using Cviptools with Cdrom

Computer Vision and Image Processing: A Practical Approach Using Cviptools with Cdrom
Comparison of edge detector performance through use in an object recognition task

Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
A Method for Objective Edge Detection Evaluation and Detector Parameter Selection

IEEE Transactions on Pattern Analysis and Machine Intelligence
SUSAN structure preserving filtering for mesh denoising

The Visual Computer: International Journal of Computer Graphics
On the Quantitative Evaluation of Edge Detection Schemes and their Comparison with Human Performance

IEEE Transactions on Computers
Efficient tracking and ego-motion recovery using gait analysis

Signal Processing
Automatic selection of edge detector parameters based on spatial and statistical measures

Computer Vision and Image Understanding
Peer group switching filter for impulse noise reduction incolor images

Pattern Recognition Letters
Ultrasound speckle reduction by a SUSAN-controlled anisotropic diffusion method

Pattern Recognition
A novel edge detection method with application to the fat content prediction in marbled meat

Pattern Recognition
Quaternion switching filter for impulse noise reduction in color image

Signal Processing
Edge detection revisited

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Short Communication: A rectilinear Gaussian model for estimating straight-line parameters

Journal of Visual Communication and Image Representation

Quantified Score

Hi-index	0.08

Visualization

Abstract

A modified Smallest Univalue Segment Assimilating Nucleus (SUSAN) algorithm based on the local gray value character of an image is presented here. Beginning with an explanation of the principle of edge detection and noise reduction, we find SUSAN algorithm is immune to all noise points but the isolated noise points. To improve this, an original edge response formulation is optimized by imposing constraint conditions. Then a set of anti-noise tests were run to compare our scheme with the original algorithm and other popular edge detectors. The results show that for Gaussian noise and salt-and-pepper noise, the improved SUSAN algorithm performs much better than the original one in view of sensitivity to noise and detection of edges, and especially for salt-and-pepper noise the improved SUSAN algorithm works best among the all detectors tested here.