基于多光谱成像和近红外点阵结构光的苹果表面缺陷快速检测方法研究

项目名称： 基于多光谱成像和近红外点阵结构光的苹果表面缺陷快速检测方法研究

项目编号： No.31301236

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 农业科学

项目作者： 黄文倩

作者单位： 北京市农林科学院

项目金额： 23万元

中文摘要： 在基于机器视觉的苹果品质检测研究中，表面缺陷的检测是难点，而区分果梗、花萼与真正的缺陷区域是最难解决且至今仍未有效解决的问题。本项目采用多光谱成像和近红外点阵结构光技术融合的方法实现苹果表面缺陷的检测，并有效区分果梗、花萼和缺陷。通过研究苹果表面缺陷在400-2500nm高光谱图像下的响应特性，确定准确表征苹果表面缺陷的最佳指纹波段图像，并研究轻微损伤和轻微腐烂这两类重要缺陷的识别方法,研究因水果表面曲率变化而造成的图像亮度不均的校正方法，构建基于多光谱成像的苹果表面缺陷检测系统；利用一种新的近红外点阵结构光编解码方法实现苹果上任意光斑的准确定位，通过光斑阵列空间位置的变化信息的快速获取，实现果梗、花萼凹陷区域的快速准确识别；研究多光谱计算机视觉系统融合的苹果表面缺陷快速一体化检测方法。研究成果有望为开发基于多光谱成像和近红外点阵结构光的苹果表面缺陷在线快速检测设备奠定理论依据和方法基础。

中文关键词： 多光谱成像；深度感知；特征波长；亮度校正；表面缺陷

英文摘要： Detection of apple's surface defects is one of the difficulties in the research of the apple's quality detection based on machine vision. However, the discrimination of stem-end/calyx from the real defects on apple is the most difficult to resolve, and there is still not an effective solution to this problem. In this study, a novel method based on multi-spectral imaging and near-infrared speckle-array encoded structured lighting was proposed to solve the problems mentioned above. The effective wavelengths could be determined by studying the response characteristics of the apple's surface defects in 400-2500nm hyperspectral images. The effective wavelengths that could be used to detect the slight bruise and slight decay are also determined. An intensity transformation method was proposed to correct the non-uniform intensity distribution on fruit's surface due to the fruit surface curvature. A multi-spectral imaging system for the apple's surface defects detection was built. Any speckle's position on the apple's surface could be accurately located through the encoding and coding of the near-infrared speckle-array encoded structured lighting. Then the rapid and accurate identification of the stem-end and calyx regions were realized through the position change of the near-infrared speckle-array on the apple's surfac

英文关键词： multispectral imaging；depth sensing；effective wavelengths；intensity correction；surface defects