脐橙分选包装表面损伤识别算法设计研究

Navel orange sorting and packaging surface damage detection algorithm design based on computer vision and image processing

研究提出了一种改进的计算机视觉识别技术与图像融合算法,并建立脐橙表面损伤识别系统,检测中从图像采集卡获得数字化的图像数据后,经过图像二值化、边缘检测和灰度拉伸处理,再对图像的行灰度均值变化曲线进行分析,加权滤波后提取特征图像,以提高脐橙分选包装的精度和速度。通过实验测试表明:边缘特征检测方法对于模糊图像的处理能力较强,算法设计中的损伤定位加快了系统的处理速度,其检测速度达到了10.5个/s,具有精度高、通用性和稳定性好等特点。

In this research an improved computer vision detection technology and image fusion method had been proposed so as to create a navel orange surface damage detection system, i.e.firstly, digitized data in detection was collected from image collection card to be processed through image binarization, edge detection and grey stretch.Then the change curve of image grey-scale average was analyzed. Finally, feature image was extracted after weighted filtering so as to improve the precision and speed of navel orange sorting and packaging. The experiment showed that edge feature detection had strong ability in blurred image processing, and that damage location in algorithm design had speeded up the system processing with 10.5 oranges per second, which was characterized by high precision, generality and good stability.