基于照度-反射模型的脐橙表面缺陷检测

水果表面缺陷是影响水果价格最主要的因素之一，目前大部分研究基于静态图像采用较复杂的算法分割水果表面缺陷。该文介绍了一种基于在线水果图像的表面亮度均一化校正及单阈值缺陷分割方法。首先，通过RGB颜色空间转换获取HIS空间图像的色调（H）分量，基于H分量建立掩模对RGB图像的R分量执行掩模去背景；然后，基于照度-反射模型，利用低通滤波获取R分量图像的亮度分量，利用此亮度分量对去背景后的R分量图像进行亮度校正；最后，利用一个简单的阈值对亮度校正后的图像进行缺陷分割。利用此算法，对416幅图像的检测结果表明总体检测正确率超过99%。该方法简单、有效，在在线水果缺陷检测中具有较大的应用潜力。

Detection of navel surface defects based on illumination-reflectance model

The presence of skin defects is one of the main influential factors on the price of fruit. Most of the researches used static images and more complex algorithm to segment defects on fruit surface. The lighting correction approach and threshold method was proposed to segment fruit surface defects. The fruit images with defects were acquired from an on-line sorting system. Firstly, hue (H) component was obtained by transforming RGB colour space to HIS colour space. The mask was created based on H component and used to remove R component image background. Then, based on illumination-reflectance model, the illumination component was extracted from R component image by low pass filter. The illumination component was used to correct illumination on R-component image. Finally, defects were successfully segmented at one time by subjecting the corrected image to a single threshold value. The experimental results with an over 99% recognition rate for 416 images showed that the proposed algorithm was simple and effective for application in real-time detection of defects on fruit.