DocumentCode :
691976
Title :
An Improved Method of Detecting Pork Freshness Based on CRR Features
Author :
Xiao Ke ; Gao Guandong ; Li Jian
Author_Institution :
Coll. of Inf. Sci. & Technol., Agric. Univ. of Hebei, Baoding, China
fYear :
2013
fDate :
16-18 Oct. 2013
Firstpage :
194
Lastpage :
197
Abstract :
In this paper, an improved pork freshness detecting method based on color features was presented according to the biochemical mechanism of pork metamorphism. The pork sample images were captured and processed by de-noisy and segmentation methods. Then, the fat areas were eliminated to reduce the influence of detection in HSV color space. A new Color Region Ratio (CRR) extraction method was presented by red ratio. 9 groups sample data were classified to conclude the principle of detecting pork freshness and computed the correlation coefficients. Finally, the PNN algorithm in neural network was performed to detect pork freshness. The experimental results showed that the color features were correlated with freshness and could detect it effectively.
Keywords :
computer vision; feature extraction; food products; image capture; image classification; image colour analysis; image denoising; image segmentation; neural nets; product quality; CRR extraction method; CRR features; HSV color space; PNN algorithm; biochemical mechanism; color feature; color region ratio extraction method; computer vision; correlation coefficient; denoisy method; fat area elimination; image capture; image classification; image processing; neural network; pork freshness detection; pork metamorphism; pork sample images; red ratio; segmentation method; Correlation; Feature extraction; Image color analysis; Image segmentation; Linear regression; Muscles; Testing; color region ratio; freshness detection; image segmentation; pork;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/IIH-MSP.2013.57
Filename :
6846613
Link To Document :
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