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基于OTSU与CANNY算法的竹片缺陷图像检测

Image Detection of Bamboo Chip Defects Based on OTSU and CANNY Algorithms

  • 摘要: 竹片缺陷检测是提升产品质量的重要工艺,利用图像自动检测竹片缺陷可以极大地提升生产效率。该文提出一种基于OTSU与CANNY算法的竹片缺陷图像检测方法,适用于拉丝片、破裂片、蛀孔片、霉片、竹青片、黑节片和三角条7种竹片缺陷检测。首先利用OTSU算法对竹片进行二值化处理、CANNY算法进行边缘检测和Hough变换进行倾斜校正,实现竹片区域提取,然后利用OTSU算法检测颜色缺陷竹片、CANINY算法进行形状缺陷检测,检测出全部缺陷竹片。研究结果表明,本文对350个7类竹片缺陷进行检测,平均准确率为95.14%,可以有效检测竹片缺陷。

     

    Abstract: Bamboo chip defect detection is an important process to improve product quality. Using images to automatically detect bamboo chip defects can greatly improve production efficiency. In this paper, an image detection method of bamboo chip defects based on OTSU and CANNY algorithm was proposed, which was suitable for seven bamboo chips such as brushed bamboo chips, cracked bamboo chips, borehole bamboo chips, moldy bamboo chips, bamboo green chips, black knot bamboo chips, and triangular bamboo chips. Firstly, the OTSU algorithm was used to binarize the bamboo pieces, the CANNY algorithm was used for edge detection, and the Hough transform was used for tilt correction to realize the extraction of bamboo pieces. Then, OTSU algorithm was used to detect color defects and CANNY algorithm was used to detect shape defects, and all defective bamboo slices were detected. The research results showed that: this paper detected 350 bamboo defects of seven types, and the average accuracy rate was 95.14%, which can effectively detect bamboo defects.

     

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