基于机器视觉的自然环境中成熟荔枝识别

研究了自然场景下成熟荔枝的识别技术.通过分析荔枝彩色图像的颜色和灰度特征,选取YCbCr颜色模型进行处理,对其Cr分量图进行阈值分割去除复杂背景,并采用形态学和连通区域标注法消除分割后的随机噪声;然后结合一维随机信号直方图分析法与模糊C均值聚类法( FCM)对处理后的荔枝图像进行聚类和分割,实现荔枝果实和果梗的识别.不同光照条件下的识别实验结果表明,算法均能有效分割出果实和果梗,综合识别率达到95.5％.

Recognition of Mature Litchi in Natural Environment Based on Machine Vision

A recognition method of mature litchi in natural scene was researched. Through analyzing the gray and color features of litchi, the YCbCr color model was selected, and by using threshold segmentation, the Cr component image was selected to remove the complex background, then morphology operation and connected region label were used to remove random noise, and then the one-dimensional random signal histogram analysis and the fuzzy C-means clustering (FCM) segmentation were used to achieve the recognition of litchi fruit and peduncle. The recognition results under different natural conditions showed that the algorithm could segment the fruit successfully and the recognition rate reached to 95.5%.