| Summary: | 碩士 === 國立屏東科技大學 === 資訊管理系所 === 104 === While purchasing agricultural products, consumers usually need opinions from professionals, such as production farmer, dealer and retailer. And the ranking category of agricultural products made by professionals will determine its selling price. Thus, the price has become one of the most important factors to inspect the quality of agricultural products in consumer market.
The aim of this research is to establish a classification model based on image recognition to assist wax apple buyers in quality inspection.
Use wax apples from Neipu township in Pingtung county as experimental subjects. The wax apples are classified by experts according to its five characters: (1) look (2) brix (3) crunchiness (4) texture and (5) maturity. We then manipulate Hue-Saturation-Intensity (eHSI) color space with different thresholds to proceed features segmentation with the exterior images of the wax apples, and extract eigenvalues based on gray level co-concurrent matrix. Finally, we inspect the wax apples by the trained support vector machine (SVM) to evaluate the applicability of the five characterization in classification.
The results of our experiments indicates our method has significant accuracy in brix classification. We have ranked the apples by its characters separately into five groups. The accuracy is between 35-45% for individual character classification. The accuracy can reach 70-80% if classification tolerance values ±1. Moreover, if we compare the classification result of brix spindle with our method, the accuracy attains to 97.93%.
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