Keywords : Hough Transform


Hybrid Technique Used for Straight Line Detection

Fawziya Mahmood Ramo; Nidhal Al-Assady; Khalil I. Al-Saif

AL-Rafidain Journal of Computer Sciences and Mathematics, 2011, Volume 8, Issue 1, Pages 89-103
DOI: 10.33899/csmj.2011.163611

Many techniques have been used in this research to detect straight line in digital image on the same samples. These techniques are:1-Hough Transform(HT), Develpoed Baron’s Method (DBM)and-Genetic Developed Baron’s Method(GDBM)
    First technique was applied as it, while the second technique was applied after performing some modification in its algorithm. The third technique hybrid DBM (second technique) with GA, after performing the three techniques the accuracy and execution time for each technique is calculated. The experiment show that the hybrid technique relatively fast and it achieves high performance. It produces (90%) detection rate. MATLAB language has been used in the implementation of this software.
 

A Suggested Point Search Algorithm for Circle Detection in Binary Images

Sundus Khaleel Ebraheem

AL-Rafidain Journal of Computer Sciences and Mathematics, 2010, Volume 7, Issue 2, Pages 79-94
DOI: 10.33899/csmj.2010.163887

Detecting circles is very important in the application of image processing especially in determining the object locations. In this paper, a new algorithm is proposed for circle detection, called Point Search Circle Detection (PSCD), which detects points and assumes them as inspection points on the circle circumference by using them to create a virtual circle to match it with the original image. Using matching operation leads to reduce computational operations and reduce the complexity and the running time of the algorithm. The proposed algorithm is highly accurate, has high speed and low storage requirements in comparing with other related algorithms. The proposed algorithm can precisely detect circles with various scales, crossed and nested circles in the binary images.
The proposed algorithm was compared with Hough Transform (HT) method for circle detection by using many images with different numbers and radius of circles and different image dimensions. The proposed algorithm was more efficient, where the average ratio of the running time for the proposed algorithm to HT method was 1:646, and the accuracy of the proposed algorithm was 100% for circles detection. Both the proposed and HT algorithms are applied by using Matlab 7.2 language, PC equipment with 1.8MHz Pentium IV processor and 512MB RAM.
 

Off-line Recognition of Unconstrained Handwritten Numerals Using Fuzzy Hough Transform

Mohammed Z. Khedher; Ghayda A.A. Al-Talib; Shayma M. Al mashhadany

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 3, Pages 211-226
DOI: 10.33899/csmj.2009.163834

A fuzzy system for handwritten numerals recognition using a fuzzy Hough transform technique is presented. The system is an off-line system since the data processed was written before the time of recognition. A data base of 480 patterns of unconstrained (free) handwritten numerals was used in the proposed system. Membership values are determined as fuzzy sets which are defined on the standard Hough transform vector.
Manhattan distance measurement has been used to measure the similarity of an input feature vector to a number of numeral pattern classes. The overall recognition accuracy of the system for the ten numerals is 95%.
 

Straight Line Detection Using Hough Transform in Grey Images

Khalil Alsaif; Sundus Khaleel Ebraheem

AL-Rafidain Journal of Computer Sciences and Mathematics, 2006, Volume 3, Issue 1, Pages 11-21
DOI: 10.33899/csmj.2006.164032

In image processing, one of the main difficulties encountered in line detection is due to the various appearances of lines to be detected. This research presents a recognition method for line using Hough Transform (HT) .Applying erosion continuously to reach one pixel width of the generated skeleton for the image. Presented results are illustrating the utility of a new approach to know the content of an image, then store it using it's parameters and reconstruct it without the need to open it.