Determination of storage time for chilled pork by using RGB color space method based on machine vision

Abstract: The storage time of chilled pork is one of the most important indexes to price of pork. However, storage time of chilled pork was determined by trainees with their own visual senses in most of the Chinese enterprises. This manual grading method demands not only intensive labor but also lacks objectivity and accuracy. The objective of this research was to develop an optimal method for determining the storage time of chilled pork based on computer vision and image processing technologies to meet the requirement of the meat industry. A practical algorithm that can be used in a chilled pork storage time determining system was proposed in this research. The chilled pork sample images were collected by a machine vision image acquisition system. The system consisted of an image acquisition device, computer, and image processing algorithm equipped into the self developed system software. The images of the chilled pork samples in a load table were captured by CCD. Light intensity was regulated through a light controller, and the distance between the camera lens and the chilled pork samples was adjusted though translation stages in the load table. Collected images were automatically stored in the computer for further image processing. First, some methods such as background removal and image denoising were adopted to preprocess the image to obtain a region of interest. In this step, the image was cropped to separate the chilled pork from the background. Then, a color difference method was used to segment the chilled pork area to obtain the area of total muscle and un-glossed muscle. Our results showed that the total and un-glossed muscle of chilled pork can be well distinguished by using binary images when R-B≤30, R-G≤30 (first feature) and R-B≤30, R-G≤30, 100≤B (second feature), respectively. Based on the first and second feature, the number of pixel in the binary images for the total and un-glossed muscle can be obtained from the color information in each pixel, and the ratio of pixel amount between un-glossed muscle and total muscle can also be obtained. We calculated the ratio of un-glossed muscle of different batches, screened the maximum ratio of un-glossed muscle of chilled pork that was stored less than three months and the minimum ratio of un-glossed muscle of chilled pork that was stored more than 12 months, respectively, and then calculated the mean of maximum and minimum value mentioned above. The mean was taken as the threshold value, and that was increased or decreased successively if the actual value was less than or equal to the threshold value mentioned above. The storage time was determined to be within three months if the actual value was greater than the threshold value, and the storage time was determined to be over 12 months. Finally, 60 chilled pork that were stored less than three months and 60 chilled pork that were stored more than 12 months were used to verify the threshold value. Our results showed that, the accuracy of the verification and determination of chilled pork that were stored less than three months (90.00%) and chilled pork that were stored more than 12 months (81.67%) were considerably improved when the threshold value was 26.8%. The results showed that the algorithm can meet the requirements of frozen pork storage time.