Study On The Key Tecnnology For Nondestructive Detection Of Clolor And Bruises Of Xinjiang Kuerle Fragrant Pears Based On Machine Vision

Kurle fragrant pear is one of the most popular fruits in abroad producted by Xinjiang. It's a very important local Economic fruit. Right now, main grading method is by manpower. For a long time working, the works would too busy to keep precision, and everyone would have different result for the same pear. Different standards not only influence the value of fragrant pear, but also influence the quality of fragrant pears and customs' contentment. Some same kind of fruits will have a good price when they have the same color. Color reflects the mature degree of fruits. The bruising of fragrant offen has the same color with normal area, they were easy to neglect. So the color grading and bruising inspection are two important targets of fragrant pears automatic grading. The paper provides a new algorithm of the Kurle fragrant pears' color and bruising non-destructive based on machine vision. The contents of each chapter are described as follows:A method for color grading and druises detection was introduced. The research status of automated classification and the need for domestic and foreign intelligence testing was analyzed.According to the study the experimental systems was desined and optimized. The equipment and software system was introduced. The method of pear grading based on machine vision was researched:H component of HSI was used to be the template of image segmentation. The image of pear apart from background was gain after thresholding and binaryzation. The statistics of average and mean square deviation of surface pixels was as the import of ANN, the color information was as the output.The rate of accuracy were both 95% by two methods.According to the characteristics of pear bruising, the bruising equipment was designed and used to simulate bruise. The machine vision technology and hyperspectral imaging technology were used to detect the slight bruisings of pear. PCA and ICA was used to analysis the dates. PCA4 was found with mainly information of bruising. The rate of accuracy was 81.0% by directly processing PCA 4. The rate of accuracy was 70.9% by processing the image which fused by 528 nm,662 nm and 740 nm. The rate of accuracy was 82.5% by processing ICA 4.At least part discusses the main achievements and conclusions and some problems for further study.