Detection Technology of Pineapple Thorn Based on Feature Extraction and Space Position
针对菠萝削皮流水线生产加工过程中菠萝表面有内刺残留，需要人工二次去除内刺的问题，采用图像处理的方法对菠萝内刺进行特征提取与空间定位，从而确定菠萝内刺的精确位置，以实现菠萝内刺的自动化去除。设计了菠萝图像采集系统以及针对当前系统的菠萝内刺检测算法。对菠萝图像进行预处理，将内刺特征从背景中分离出来剔除干扰特征，并将内刺的轮廓作为提取特征。轮廓的面积和轮廓的圆度作为描述子，菠萝内刺轮廓最小外接矩形的中心坐标作为菠萝内刺在图像中的位置，利用菠萝外轮廓将内刺的二维坐标转换成三维坐标从而精确定位菠萝内刺。对比实验表明：菠萝内刺检测算法准确率明显高于传统的斑点检测算法，内刺中心位置拟合精度较高，检测最大误差为0.63 mm，平均检测误差为0.33 mm。研究表明，平均检测速度和精度都能满足菠萝内刺去除工序的需要，这为菠萝流水线加工过程中的内刺去除提供一定的技术基础。
During the production and processing of pineapple peeling line, inner thorns remain on the pineapple surface, which require manual secondary removal. To address this, an image processing method is adopted to extract features and spatially locate the inner thorns of pineapple, to determine their precise location for automatic removal of the thorns. Accordingly, a pineapple image acquisition system and a corresponding pineapple inner thorn detection algorithm are designed. The pineapple image is preprocessed to separate the inner thorn features from the background, eliminating the interfering features, and the contour of the inner thorn is used as the extracted feature. The area of the contour and the roundness of the contour are used as descriptors, and the center coordinates of the smallest outer rectangle of the pineapple inner thorn contour are used as the position of the pineapple inner thorn in the image, while the outer contour of the pineapple is used to convert the two-dimensional coordinates of the inner thorn into three-dimensional coordinates to precisely locate the pineapple inner thorn. The comparison experiments show that the accuracy of the pineapple inner thorn detection algorithm is significantly higher than that of the traditional speckle detection algorithm. In addition, the accuracy of fitting the center of the inner thorn is higher, with the maximum detection error of 0.63 mm and average detection error of 0.33 mm. The study shows that the average detection speed and accuracy can meet the needs of the pineapple inner thorn removal process, which provides a certain technical basis for the inner thorn removal in pineapple assembly line processing.
李莹, 袁浩, 王凯彬, 何自芬, 董耀. 基于特征提取与空间定位的菠萝内刺检测技术[J]. 激光与光电子学进展, 2023, 60(22): 2212004. Ying Li, Hao Yuan, Kaibin Wang, Zifen He, Yao Dong. Detection Technology of Pineapple Thorn Based on Feature Extraction and Space Position[J]. Laser & Optoelectronics Progress, 2023, 60(22): 2212004.