DocumentCode :
633943
Title :
Spring gauge system by using R-radius corner detection
Author :
Mao-Hsu Yen ; Hawyun Shin ; Chih-Cheng Lai
Author_Institution :
Dept. of Comput. Sci. & Eng., Nat. Taiwan Ocean Univ., Taipei, Taiwan
fYear :
2013
fDate :
14-17 July 2013
Firstpage :
276
Lastpage :
281
Abstract :
Feature detection is widely used in image processing, image recognition and machine vision. Points, lines and regions are usually understood as features. In addition, point features are such as object corners because of their variances are not to be impacted by geometry property, and they are simple to recognize for every man. Hence, more and more individual corner detections are proposed. However, rounded corners are seldom discussed in image recognition, and we find that helical compression spring is a great object of study. In this paper we propose rounded corner detection for detecting outside diameter of helical compression spring. The method uses slope comparison to search sites of rounded corner on the helical compression spring image. Through experiments and statistics for computing the outside diameter of spring, this method can steadily detect the rounded corners between 0 degree and 45 degrees, and the deviation of diameter is less than 0.3 percent. Furthermore, it does not have complicated operations in steps, so it can provide stable and accurate results swiftly.
Keywords :
feature extraction; image coding; object detection; R-radius corner detection; feature detection; geometry property; helical compression spring; image processing; image recognition; line feature; machine vision; point feature; region feature; slope comparison; spring gauge system; Abstracts; Image edge detection; R-radius; R-radius corner detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2013 International Conference on
Conference_Location :
Tianjin
ISSN :
2158-5695
Print_ISBN :
978-1-4799-0415-0
Type :
conf
DOI :
10.1109/ICWAPR.2013.6599330
Filename :
6599330
Link To Document :
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