水果表面亮度不均校正及单阈值缺陷提取研究

Correction Algorithm of Illumination Nonuniformity on Fruit Surface and Defects Extraction Using Single Threshold Value

提出了一种水果表面亮度不均校正算法。以脐橙为研究对象,首先提取R分量图像并除去背景后获得原始图像;然后根据照度-反射模型,利用低通滤波获得该图像的入射分量图,将此入射分量图作为该图像的亮度图像;最后,原始图像与亮度图像相除后即为亮度校正后的图像。基于亮度校正后的图像,利用单阈值对水果表面缺陷一次性成功分割。利用开发的算法对正常样本和带有10类不同缺陷的样本共计788幅图像进行处理,总体识别正确率达到97%。

An algorithm was proposed to overcome the difficulty that defects could not be successfully segmented at one time due to illumination nonuniformity on fruit surface.Navel orange was selected as experiment object.Firstly,the R-component image of navel orange was extracted and original image was obtained by removed R-component image background.Then,incident component of original image was obtained by low pass filtering based on illumination-reflectance model.The incident component was considered as illumination image of original image.Finally,the corrected image was computed by original image dividing by illumination image.Defects were successfully segmented at one time by a threshold value.The sound samples and samples with other ten types of peel diseases were detected by using the proposed method.The experimental result showed that the recognition rate was over 97% based on 788 obtained images.