球体图像灰度变换模型及其在柑桔图像校正中的应用

由于水果形状不规则，在利用机器视觉和图像处理技术进行水果品质检测和自动分级过程中，会产生图像失真现象。针对这一问题，通过分析在6个位置采集的3种不同尺寸、19种不同表面颜色的标准试验球体的图像，研究了球体的大小、表面颜色和图像采集位置等因素对球体图像灰度失真的影响，并分别建立了位于摄像视区中心的球体图像的灰度校正模型和偏离摄像视区中心的球体图像的灰度校正模型，模型的相关系数R²分别为0.796和0.842。最后，采用该模型在MATLAB软件平台上构建了柑桔图像的灰度校正算法。试验结果

Gray level transform model of ball image and its application in citrus image correction

In the process of quality inspection and automatic classification of fruit based on machine vision, fruit image is distorted due to the three-dimensional shape of fruit. Aimed to reduce this image distortion, the images of 57 balls, which were divided into three groups with the diameters of 75, 60, and 40 mm, respectively, and every group consisted of 19 balls with different colors, were captured at 6 different positions. The influences of size, color and image capturing position of a ball on the image gray level distortion were studied. Image gray level correction model of ball at the center of camera view field, and image gray level correction model of ball not at the center of camera view field, were developed, and the correlation coefficients R² of the models were 0.796 and 0.842, respectively. Based on these models, the gray level correction algorithm of citrus image was set up using MATLAB software, and the experimental results proved that the gray level correction model and algorithm were valid and reliable.