Title : 
Study on Tire Sidewall Marking Recognition Based on Moments
         
        
            Author : 
Yu Xia ; Gou Panjie ; Su Liang
         
        
            Author_Institution : 
Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang, China
         
        
        
        
        
        
            Abstract : 
Tire sidewall marking are the information for customer usage, safety, regulatory of national and manufacture internal trace ability. The consequence is high severity when marking are not correct. Hence, the marking verification is very important, because tire sidewall marking is arc-distribution, it is difficult to extract the feature vector. To solve this problem, a moment-based method is presented in this paper, which avoids stretching and correction during the recognition. The extracted vector is scale and rotation invariance. Experimental shows that the recognition rate of presented method is above 94.7%, which indicates that the method can be put into partial application to substitute for manual verification.
         
        
            Keywords : 
feature extraction; object recognition; production engineering computing; safety; tyres; arc-distribution; customer usage; feature vector extraction; manufacture internal trace ability; marking verification; moment-based method; national internal trace ability; rotation invariance; safety; scale invariance; tire sidewall marking recognition; character recognition; feature extraction; moment; tire sidewall marking;
         
        
        
        
            Conference_Titel : 
Intelligent Networks and Intelligent Systems (ICINIS), 2013 6th International Conference on
         
        
            Conference_Location : 
Shenyang
         
        
            Print_ISBN : 
978-1-4799-2808-8
         
        
        
            DOI : 
10.1109/ICINIS.2013.12