局部二值模式在连铸坯表面缺陷识别中的应用

Application of local binary patterns to surface defect recognition of continuous casting slabs

  • 摘要: 为了解决传统的图像识别算法无法准确识别铸坯表面缺陷的问题,提出一种考虑图像相邻像素影响的改进的多块局部二进制算法(MB-LBP).该算法将原始图像分成多个小区域,每个小区域再做等分,并计算平均灰度值,再运用局部二进制模式算法进行计算.对现场采集到的连铸坯表面裂纹、划伤、压痕、凹坑和无缺陷共五类1697个样本进行实验,整体识别率达到94.9%,而传统局部二进制模式算法的识别率为89.1%,说明本文算法具有更好的鲁棒性和抗噪能力.

     

    Abstract: To solve the detection problems of slab surface defects by conventional image recognition algorithms, this article introduces an improved multi-block local binary pattern algorithm which considers the image's pixels. In this algorithm, the original image is divided into several small regions, each small region is equally divided, and the average gray value is calculated. Then the local binary pattern algorithm is used. Five different kinds of 1697 samples gathered from a production line of slabs were examined, including cracks, scratches, indentations, dents, and no defect. The recognition rate reaches 94.9%, while the recognition rate of the traditional local binary pattern method is 89.1%. The results show that the proposed algorithm has the characteristics of high precision, better robustness and noise immunity.

     

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