Title :
Applying Grey relation method to determine the “carbon black” ranking of rubber samples
Author :
Lin, Tzu-Yuan ; Tong, Chia-Chang ; Wen, Kun-Li
Author_Institution :
GOTECH Testing Machine Inc., Tainan
Abstract :
"Carbon black" is the major influential factor in categorizing the quality rank of rubber. This paper presents a new approach to simplify the ranking procedure with limited samples by using Grey relational grading method while the ranking accuracy is ensured. The proposed approach is described as follows: First, rubber samples are sliced and snapshot into black & white images. These images are further enhanced by digital image processing methods before applying this new clustering approach. Then, the "carbon black" of a sampled rubber image is classified into ten ranks according to the method B of ISOH345 document. The measured data are processed by using the algorithm of partial Grey relational grading methods. The "carbon black" ranking of rubber is obtained by sorting and determining the maximum value of Grey relational algorithm. In order to verify this new approach, test results are compared to the results taken by standard statistical method as reference. The results confirm that this new approach can use fewer samples and preserve the ranking accuracy.
Keywords :
grey systems; image classification; image enhancement; pattern clustering; production engineering computing; quality control; rubber; rubber industry; ISOH345 document; black-and-white images; carbon black ranking; clustering approach; digital image processing; grey relational grading method; image classification; image enhancement; rubber quality rank categorization; rubber samples; Cities and towns; Image analysis; Intelligent systems; Machine vision; Measurement standards; Optical reflection; Rough surfaces; Rubber; Surface roughness; Testing;
Conference_Titel :
Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-1294-5
Electronic_ISBN :
978-1-4244-1294-5
DOI :
10.1109/GSIS.2007.4443239