基于灰度带比例的优质西瓜子识别算法研究与实现

Research and implementation of recognition algorithm based on gray scale of watermelon seeds

为了分拣出正常西瓜子,根据西瓜子的特点,提出了针对西瓜子的基于灰度带比例的特征值提取算法,并在CCD色选机上进行了试验验证。在瓜子图像预处理中,先对瓜子图像进行对比度自适应的直方图均衡化,而后对瓜子的二值化图像进行中值滤波。在瓜子分类方面,采用灰度带比例作为分类特征量,并在CCD色选机上进行特征量分类训练,最终分检出正常瓜子,识别率达到95%。该算法为该西瓜子的分类识别提供了理论支持和技术实现。

In order to sort the normal watermelon seeds, according to the characteristics of watermelon seeds, a feature extraction algorithm based on the gray scale was proposed, and its verification tests was carried out on a CCD color sorter. In the seeds image pre-processing, the contrast adaptive histogram equalization of the seeds image was executed. Then, after the median filter of the histogram equalization images, the value of the gray scale of the watermelon seeds was extracted as the classification characteristic quantity. The classification characteristic quantity was trained on the CCD color sorter, and the normal seeds were picked out finally with 95% recognition rate. The algorithm can provide theoretical support and technical realization for the classification and recognition of watermelon seeds.