【作者】 刘金帅；

【导师】 赖惠成；

【作者基本信息】 新疆大学 ， 通信与信息系统， 2012， 硕士

【摘要】 采棉机器人是未来机械采棉的发展方向，具有广阔的应用前景。开展采棉机器人的研究对于市场需求、提高经济效率和降低劳动强度都有着重要的现实意义。自然环境下成熟棉花的识别与定位技术是采棉机器人视觉系统的关键技术，本研究以田间成熟期的棉花为研究对象，主要的研究内容包括：在成熟棉花识别方面，本研究提出了一种基于YCbCr颜色空间下利用Fisher判别分析的成熟棉花的分割策略。利用摄像机拍摄不同光照下的棉花图像，对比分析了在RGB、HSV和YCbCr颜色空间下利用Fisher判别分析的分割效果，并与目前已提出的几种棉花分割策略做了对比分析。为了保证成熟棉花的边界信息，本章采用贴标签的处理方法很好的将成熟棉花区域分割出来。实验证明本章提出的方法有效避免了阳光直射和阴影的干扰，分割准确率是90.44%。在成熟棉花定位方面，本研究对双目立体视觉模型、摄像机成像模型和标定理论进行了研究，采用张正友标定方法对本研究的双目立体视觉系统进行了标定。提出了多目标情况下确定各个采摘点的方法，采用了基于区域相似匹配和约束条件的方法进行匹配。本研究根据三角测量方法恢复特征点三维坐标，并对该方法进行了分析和实验，实验结果表明该方法能够满足采棉机器人视觉系统的需求。由于SIFT算法的复杂度高，提取的关键点不是角点，本研究先采用Harris算子提取分割后的棉花图像的特征点，然后计算每个特征点的SIFT向量的描述符，后面使用SIFT特征匹配方法匹配，实验表明本方法得到的匹配点更适合恢复棉花的形态。更多还原

【Abstract】 The application of cotton-picking robot will be a development trend of agriculturalmechanization and has a great prospect. Researches in cotton-picking robot have greatsignificance for reducing working intension, increasing economy efficiency and adaptingrequirement of market. The cotton-picking robot, the cotton identification andlocation technology in the natural environment is the key technology. The maturity cotton in thenatural environment was the research object. The two point in the research were as follow:In recognition of the mature cotton, the study proposed a mature cotton segmention strategybased on the YCbCr color space and Fisher discriminant analysis. First the research shoted thescene under different illumination use CCD camera, then contrasted analysis of segmentationresult in RGB,HSV, and YCbCr color space using Fisher discriminant analysis, and comparedwith proposed segmentation strategy. In order to ensure the boundaries information of the maturecotton, the research used the method of labeling to denoise. The simulation result that the cottoncould be separated exactly from background by the above algorithm whether the cotton wasexposed to the sunlight or the shadow with an accuracy of90.44%.In location of the mature cotton, the research studied the stereo vision theory, cameraimaging model and calibration theory, and used Zhang Zhengyou calibrating method to calibratethe binocular stereo vision system. The research proposed a method to determine picking points,used region-match and specific constraints to match them, accorded to the triangulation method torestore the three-dimensional coordinates. The experimental results that the method the methodcan meet the demand for cotton-picking robot vision system. Due to the key points of the SIFTalgorithm is not corners, so the research used Harris method to extract corners in segmented cottonimage, and then calculated the SIFT descriptor vector of each feature point, and finally used theSIFT matching method to match them. The experiments showed that the matching point obtainedby this method was more suitable for the restoration of the morphology of the cotton.更多还原