Color Model Analysis and Recognition for Parts of Citrus Based on Exploratory Data Analysis

Abstract:

Aiming at the characteristics of various parts of mature citrus, uncertainty and variability of light and environment, various parts of citrus image data had been conducted to exploratory data analysis and identify. The characteristics of exploratory data analysis method and the principle of citrus recognition based on color channel were analyzed. The flow chart of exploratory data analysis of citrus image data was provided. The acquired citrus images were divided into three different lighting conditions: front-lighting, normal light and backlighting. The image data of citrus fruits, stems and leaves were collected. According to the image data, the sorted box-plot on color component for all parts of citrus based on six kinds of color space were designed. With data analysis about the graphics of box-plot, a vision model of recognition of different parts of citrus was given based on I2 color component of I1I2I3 color space. When the threshold value of I2 was 0.3, the branches, the leaves and the grass in complex background could be removed and thus citrus fruits and their background could be segregated. Finally, 300 differently illuminated citrus images were collected in natural circumstance as test objects, all rip citrus fruits were effectively recognized based on the vision model of I2 color feature, and the citrus fruits recognition ratio was 98.4%. Also the situation was confirmed that the fruit stems and leaves could not be distinguished only relying on color feature because of their similarity color.