Ling Ma; Yumin Liu; Huiqin Jiang; Zhongyong Wang; Haofei Zhou

An Improved Method of Geometric Hashing Pattern Recognition

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Author(s)

Ling Ma ^1,* Yumin Liu ² Huiqin Jiang ³ Zhongyong Wang ³ Haofei Zhou ²

1. Fast Corporation 2791-5 Shimoturuma Yamoto, Kanagawa Japan

2. Business School and Digital Medical Image Technique Research Center Zhengzhou University, Zhengzhou, China

3. School of Information Engineering and Digital Medical Image Technique Research Center Zhengzhou University, Zhengzhou, China

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2011.03.01

Received: 23 Feb. 2011 / Revised: 3 Apr. 2011 / Accepted: 10 May 2011 / Published: 8 Jun. 2011

Index Terms

Object recognition, Geometric hashing, Invariant matching, Shape profile

Abstract

Geometric hashing (GH) is a general model-based recognition scheme. GH is widely used in the industrial products assembly and inspection tasks. The aim of this study is to speed up the geometric hashing pattern recognition method for the purpose of real-time object detection applications. In our method, a pattern is decomposed into some sub-patterns to reduce the data number in hash table bins. In addition, the sub-patterns are recorded in a plurality of hash tables. Finally we improve the recognition performance by combining with image pyramid and edge direction information. To confirm the validity of our proposed method, we make a complexity analysis, and apply our method to some images. Both complexity analysis and experiment evaluations have demonstrated the efficiency of this technique.

Cite This Paper

Ling Ma, Yumin Liu, Huiqin Jiang, Zhongyong Wang, Haofei Zhou, "An Improved Method of Geometric Hashing Pattern Recognition", International Journal of Modern Education and Computer Science(IJMECS), vol.3, no.3, pp.1-7, 2011. DOI:10.5815/ijmecs.2011.03.01

Reference

[1]D.H. Ballard. Generalizing the Hough Transformation to Detect Arbitrary Shapes. Pattern Recognition.Vol.13 No.2. pp111-122. 1981.
[2]H.J. Wolfson and I. Rigoutsos. Geometric hashing: an overview. IEEE Computational Science and Engineering, 4(4):10–21, Oct-Dec 1997.
[3]Hunny Mehrotra. Banshidhar Majhi. Phalguni Gupta.Robust iris indexing scheme using geometric hashing of SIFT keypoint.Journal of Network and Computer Applications, Vol. 33, No. 3, 2010, pp 300-313.
[4]Md.Saiful Islam,Andrzej Sluzek. Relative scale method to locate an object in cluttered environment.Image and Vision Computing.Vol. 26, No. 2, 2008, pp 259-274.
[5]K.Yasuhiro,O.Tomonob and O.Takenao. Partial Geometric Hashing for Retrieving Similar Interaction Protein Using Profile, Information Technology, 2007. ITNG '07. Fourth International Conference on Digital Object . 2007, pp589 – 596.
[6]X.Guo and A. Hu. The Automatic Fuzzy Fingerprint Vault Based on Geometric Hashing: Vulnerability Analysis and Security Enhancement , Multimedia Information Networking and Security, 2009. MINES 09. 2009 , pp62 – 67.
[7]John canny. A computational approach to edge detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, PAMI-8(6):679–698, Nov. 1986.
[8]P. Anandan,“A computational framework and an algorithm for the easurement of visual motion,” International Journal of ComputerVision, vol. 2, no. 3, 1989, pp. 283-310.
[9]J. Y. Bouguet, Pyramidal Implementation of the Lucas Kanade FeatureTracker, Intel Corporation, Microprocessor Research Labs, 2000.

International Journal of Modern Education and Computer Science (IJMECS)