基于计算机视觉的苹果生长姿态估算多方法融合

Estimation Method of Apple Growing Attitude Based on Computer Vision

为了避免机械手在采摘过程中因缺少苹果生长姿态信息造成对苹果和枝干的损伤,提出了一种苹果生长姿态估算方法。利用纹理和颜色特征两步法实现背景分离后,采用链码跟踪法获得轮廓;阐述了二阶中心矩法、最短距离法、斜率方差法和三点一线法4种苹果姿态识别方法,并比较了4种方法的识别率。为了提高姿态的识别率,综合4种方法进行决策融合,识别苹果姿态。研究结果表明,基于4种方法的融合决策识别苹果的正确率高于单独使用任何一种方法,正确率达到了90%。

In order to avoid damaging apples and branches caused by manipulator during the picking operation,for the absence of attitude information,an apple＇s attitude estimation method was put forward.After the apple object was segmented from background with the two-step algorithm based on the characters of color and texture,the freeman chain code algorithm was used to extract one-pixel fruit contour.Then least distance method,least slope variance method and three collinear points＇ method were given,and the recognition rates of three methods were compared.At last,for the purpose of improving recognition rate,decision method based on fusion of four methods was proposed.The research results showed that the recognition rates by using four methods were higher than using any one of methods separately,and the right recognition rate could reach to 90%.