The Application of Randomized Hough Transform in Ellipse Image Detection

2010 ◽  
Vol 159 ◽  
pp. 388-392
Author(s):  
Xin Yu Hu ◽  
Zuo Bing Chen ◽  
Dao De Zhang ◽  
Guang You Yang

As the traditional Hough transform has such defects as large storage space and long computing time in ellipse detection, an improved randomized ellipses detection method based on least squares was presented, which utilizes the least square approach to fit the ellipse and combines both of the advantages of the random Hough transform and the least square. By setting appropriate distance threshold of the candidate ellipse and the threshold of edge points, the method of ellipse detection decreases the number of random sampling and the invalid calculation of cumulation in the process of Hough transform. The results show that the method doesn’t require large storage space, has good ability to overcome the noise and realizes the fast detection for the single ellipse and defective ellipse.

2005 ◽  
Vol 295-296 ◽  
pp. 277-282
Author(s):  
Ji Wen Cui ◽  
Jiu Bin Tan

Hough Transform (HT) is an image edge detection technique which is widely used in pattern recognition and computer vision. In this paper the fundamental principle of HT is analyzed and the defect of HT and Randomized Hough Transform (RHT) is indicated. An algorithm based on RHT and the information of grayscale and gradient in image is proposed. It uses the property of the pattern and is mainly used for detection of circle and arc contour measurement. This algorithm can decrease memory usage in computer by a multi to one mapping, accelerate the calculation speed by parallel algorithm, improve the edge detection accuracy by subpixel division, obtain the parameters of object by applying least square fitting algorithm. Based on the principle, a measurement system with high accuracy and efficiency in image capturing and processing is developed. Experiments are carried out in the system. The result of experiment has certified the feasibility and validity of the algorithm.


Sign in / Sign up

Export Citation Format

Share Document