| Currently, the quality grading of beef is still done by human visual inspecting. There are series of problems in manual operation due to the subjectivity, low-level efficiency, and some other shortcomings. Consequently, studying automatic grading method of beef quality based on the computer vision technology is of great importance, which can resolve the problems brought by manual activity and promote automation level of beef cattle industry.A device used for capturing system of beef image was designed and developed and then images of beef rib-eye cross-section were collected by using this device. Following pre-processing of images, the extraction of the beef rib-eye images was carried out. It laid a good foundation for classifying the beef muscle color and fat color. The main research work in this dissertation was outlined as follows:1. A device used for capturing system of beef image was designed and produced which laid a good foundation for classifying the beef quality. It includes sofeware development and hardware design. First of all, the digital camera was developed on the basis of the SDK to devise the software. The uniformity, luminance given by this device were analyzed and studied. Experimental results showed that good, uniform and color reproduction illumination could be provided by this device.2. Image processing technique was applied to the pre-processing of obtained images, involving in denoising, removal of the background, the segmentation of the effective determining area etc.. Firstly, space-domain low passing filtering method was adopted to reduce the noise of beef rib-eye cross-section images. Secondly, the method of segmentation based on Otsu and improved CV model was used to segment the background of image. Lastly, some image processing methods, OSTU, all direction erosion and expansion techniques and "AND" operation, were used to segment the effective determining area for beef quality grading. Results showed that satisfied segmentation was obtained. |
PDF Full Text Request