Title : 
The fresh classification of pork detection based on multi-data fusion
         
        
            Author : 
Guo Peiyuan ; Bi Song ; Chen Tianhua ; Xu Guannan ; Liu Xing
         
        
            Author_Institution : 
Coll. of Comput. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
         
        
        
        
        
        
            Abstract : 
In order to find a quick valid scientific way to identify meat freshness, the article analyses the measuring mechanism of identifying to fresh degree of meat, and designs one set of intellectual detection and identification system that is based on electronic information technology, photoelectric detection technique, image processing technology and neural network model recognition technology. In order to achieve the freshness of the pork inspection classification identification, neural network technology micro-parameters of non-coherent multi-data fusion detection methods was Researched.
         
        
            Keywords : 
biology computing; biomedical optical imaging; food products; image classification; inspection; neural nets; object detection; photoelectricity; production engineering computing; sensor fusion; electronic information technology; identification system; image processing technology; intellectual detection system; meat fresh classification; neural network model recognition technology; noncoherent multidata fusion detection methods; photoelectric detection technique; pork detection; pork inspection classification identification; Artificial neural networks; Image color analysis; Microorganisms; Proteins; Software; Standards; Transforms; Identifying Meat Freshness; Neural Network; Pattern-Recognition; Photo-electricity Measuring; Plaque Area;
         
        
        
        
            Conference_Titel : 
Control Conference (CCC), 2010 29th Chinese
         
        
            Conference_Location : 
Beijing
         
        
            Print_ISBN : 
978-1-4244-6263-6