【摘要】 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%。更多还原

【Abstract】 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.更多还原