H. Wen’s scientific contributions

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Publications (2)


Paper Defects Image De-noising Algorithm Based on Holomorphic Filtering and Discrete Cosine Transform
  • Article

May 2018

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2 Reads

Chung-kuo Tsao Chih/China Pulp and Paper

Y.-H. Qu

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W. Tang

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H. Wen

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T. Lei

Aiming at the problems of the light-source noise in the process of paper defeats collection,the paper analyzed the characteristics of the light source noise and proposes a de-noising Algorithm based on holomorphic filtering and DCT transform. Firstly, blocking the image; then, taking logarithm operation and DCT transform of each image block and transforming them to frequency domain. Next, Gaussian holomorphic filteringused to remove noise interference. Finally, IDCT transform and exponential operation are used to restore them to the spatial domain. The experimental results showed that the algorithm could effectively remove various kinds of light-source noise and enhance the paper defect area. © 2018, China National Pulp and Paper Research Institute(CNPPRI). All right reserved.


Application of Edge Tracking Algorithm to Multiple Paper Defects Segmentation

August 2017

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3 Reads

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1 Citation

Chung-kuo Tsao Chih/China Pulp and Paper

Aiming at the problem of multiple paper defects segmentation in web inspection system, an improved edge tracking algorithm was proposed in this paper. This algorithm firstly tracked the chain code of paper defect edge, and recorded the coordinates to get the bounding rectangle of the image, then extracted defect image of each rectangle. The results showed that the presented algorithm not only could effectively extract the edge of paper defect, but also precisely completed the segmentation of multiple paper defects. © 2017, China National Pulp and Paper Research Institute(CNPPRI). All right reserved.

Citations (1)


... For the boundary tracking and application of multi-level grayscale image [7][8][9][10][11][12][13][14] , the determination of the starting search point, the boundary identification standards and the selection of search criteria are different from the boundary tracking algorithm based on the binary image. Generally, it is firstly to calculate the gradient map of the image by differential operator, and then to find the pixel point with the largest gradient as a starting search point, and then to find the second boundary point from the 8 neighborhoods of the starting point. ...

Reference:

Multi-Objective Boundary Tracking Method in Grayscale Image
Application of Edge Tracking Algorithm to Multiple Paper Defects Segmentation
  • Citing Article
  • August 2017

Chung-kuo Tsao Chih/China Pulp and Paper