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| Segmentation Algorithm of Paper Defect Images Based on RPCA |
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| DOI：10.11981/j.issn.1000-6842.2017.02.39 |
| Key Words:data redundancy; RPCA; image segmentation; paper defect detection |
| Fund Project:陕西省自然科学基础研究计划项目(2014JM8329)；陕西省教育厅专项科研计划项目(14JK1092)；咸阳市科技计划项目(2011K07-03)；陕西科技大学博士科研启动基金(BJ10-10)。 |
| Author Name | Affiliation | | 亢 洁 | 陕西科技大学电气与信息工程学院,陕西西安,710021 | | 潘思璐* | 陕西科技大学电气与信息工程学院,陕西西安,710021 | | 王晓东 | 陕西科技大学电气与信息工程学院,陕西西安,710021 |
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| Abstract: |
| In the practical detection, the resolution of collected image is getting higher and higher, resulting the data dimension is too large in image processing, a paper image segmentation algorithm based on Robust Principal Component Analysis (RPCA) was proposed in this paper. The matrix of paper defect image could be decomposed into sparse matrix and low rank matrix. In the subsequent detection, just selecting the image corresponded by the sparse matrix for detection could meet the requirements of paper defect detection, and reduce the amount of computation effectively, and eventually reduce the detection time of the whole paper defect. The simulation results showed that the proposed algorithm could be used for the segmentation of the paper image and had good segmentation performance. |
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