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局部二值模式在連鑄坯表面缺陷識別中的應用

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

  • 摘要: 為了解決傳統的圖像識別算法無法準確識別鑄坯表面缺陷的問題,提出一種考慮圖像相鄰像素影響的改進的多塊局部二進制算法(MB-LBP).該算法將原始圖像分成多個小區域,每個小區域再做等分,并計算平均灰度值,再運用局部二進制模式算法進行計算.對現場采集到的連鑄坯表面裂紋、劃傷、壓痕、凹坑和無缺陷共五類1697個樣本進行實驗,整體識別率達到94.9%,而傳統局部二進制模式算法的識別率為89.1%,說明本文算法具有更好的魯棒性和抗噪能力.

     

    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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