Machine Vision based Image Analysis for the Estimation of Pear External Quality

The research on real time fruit quality detection with machine vision is an attractive and prospective subject for improving marketing competition and post harvesting value-added processing technology of fruit products. However, the farm products with different varieties and different quality have caused tremendous losses in economy due to lacking the post-harvest inspecting standards and measures in China. In view of the existing situations of fruit quality detection and the broad application prospect of machine vision in quality evaluation of agricultural products in China, the methods to detect the external quality of pear by machine vision were researched in this work. It aims at solving the problems, such as fast processing the large amount of image information, processing capability and increasing precision of detection, etc. The research is supported by the software of Lab Windows/CVI of NI Company. The system can be used for fruit grading by the external qualities of size, shape, color and surface defects. Some fundamental theories of machine vision based on virtual instrumentation were investigated and developed in this work. It is testified that machine vision is an alternative to unreliable manual sorting of fruits.