Based on the Hamilton Improved Circle of Scraps Joining Together

Chao Wei Zhang

doi:10.4028/www.scientific.net/AMM.536-537.245

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Application of an Improved Algorithm for Denoising of Wavelet Threshold in Palmprint Recognition
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Association Degree Optimization Model and Algorithm for the Reconstruction of Cross-Cut Shredded Paper
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Multi-Fractal Spectrum and their Applications in Metal Fracture Surface Images Feature Extraction
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Based on the Hamilton Improved Circle of Scraps Joining Together
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Study on Network Video Monitoring System for Industrial Field
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A Novel Technique of Error Analysis Based on Test Case Combination
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Apply Two Methods to Measure Engine Noise Source Identification
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 536-537Based on the Hamilton Improved Circle of Scraps...

Based on the Hamilton Improved Circle of Scraps Joining Together

Abstract:

By using Hamilton improved circle, transversely and longitudinally cut up paper join together. By scanning image and image extraction techniques, the images of shredded paper are obtained. The process of shredding splicing is mainly divided into two parts, the image preprocessing and edge matching. Then the images conver into grey value matrixes and binarization are implemented on the image with appropriate threshold. The images of shredded paper are classified into nineteen lines. With the shortest Euclidean distance between the edge of shredding and Hamilton improved circle, shredded paper is transversely spliced. The test shows that accuracy is as high as 100%.

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Periodical:

Applied Mechanics and Materials (Volumes 536-537)

Pages:

245-248

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.536-537.245

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Online since:

April 2014

Authors:

Chao Wei Zhang*

Keywords:

Edge Matching, Euclidean Distance, Hamilton Improved Circle, Projection Constraints

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* - Corresponding Author

References

[1] Fei Ma, Hailian Lv, Guo Shi. Printed Chinese Character Recognition Based on the Shortest Euclidean Distance Matching. Journal of PingDingShan Institute, 2012, 27 (2); 70-70.

Google Scholar

[2] Haiyan Jia, Liangjia Zhu. A Shredding Automatic Splicing of Shape Matching Method. The Computer Simulation, 2006, 23 (11); 180-180.

Google Scholar

[3] Beibei Zheng. The Improved Genetic Algorithm Applied to Fragments Stitching. Computer and Modern, 2011, (5); 52-56.

Google Scholar

[4] Zhizhong Luo. Based on the Characteristics of Text Document Scraps of Semi-auto Stitching. Computer Engineering and Application, 2012 (5), 13207-207.

Google Scholar

[5] Qian Dong. Image Fragments Stitching Based on OpenCV. Science Technology and Engineering, 2010, (22); 5429-5429.

Google Scholar

[6] Yuhua Zhao, Weimin Ren, Kebai Li. About Hamilton Shortest Path Algorithm. DongFang Review, 2004, 19 (1); 42-46.

Google Scholar