Robot Vision System Based on Image Model Feature Extraction

Yun Zhao

doi:10.4028/www.scientific.net/AMM.602-605.1485

Paper Titles

Research and Application on Central Air Conditioning Control System
p.1468

Design of Central Air Conditioning Control System
p.1472

Kinematic Research of the Multi-Motion Pattern Bionic Mechanism
p.1476

Design Analysis of Electrical Control System for the Gear Teaching Simulator
p.1481

Robot Vision System Based on Image Model Feature Extraction
p.1485

The Self-Synchronization Theory of a Vibrating System by Two-Motor Driven with Isolation Frame
p.1490

Auto Parts Welding Line Based on Failsafe PLC
p.1495

Research of Test Method for the Robustness of Large-Scale Network Control Software
p.1499

Bionic Research and it’s Application of Artificial Lateral Line System
p.1503

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Robot Vision System Based on Image Model Feature...

Robot Vision System Based on Image Model Feature Extraction

Abstract:

Algorithm encryption of wavelet image which has excellent localization property in time domain and frequency domain can locate graphic information having different directional characteristics into any precision level in certain extent. It has feature matched with human visual characteristics because of the disappearance of blocking effect and the noise. The article first analyzes the wavelet transformation principle of image model in feature extraction process and the second iteration process. Dynamic image feature extraction model can be established using this method in robot vision system. The result of envelope is more realistic and the effect is obvious. The application of the diversity training to project and contrast, the comparison precision is high and relative error is low.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

1485-1489

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.1485

Citation:

Cite this paper

Online since:

August 2014

Authors:

Yun Zhao*

Keywords:

Feature Extraction, Image Model, Robot Vision, Wavelet Transform (WT)

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

* - Corresponding Author

References

[1] Chun Chen. Computer image processing technology and algorithms [M]. Tsinghua University Press, 2013: 83-89.

Google Scholar

[2] Xiaoxia Zheng, Weijian Li. Image Retrieval technology based on texture feature extraction [J]. Heilongjiang Institute of Engineering , 2005, 19(4): 17-19.

Google Scholar

[3] Yepeng Guan, Weikang Gu. Research on the self-extraction algorithm of two-dimensional image feature points [J]. Sensing Technology Journal , 2014(3): 45-47.

Google Scholar

[4] Fabien A. P. Petitcolas, Ross J. Anderson and Markus G. Kuhn. Information hiding- a survey"[C]. Proceedings of the IEEE, special issue on protection of multimedia content, 2009: 1062-1078.

Google Scholar

[5] Fridrich J, Goljan M, Hogea D. Steganalysis of JPEG images: breaking the F5 algorithm[C]. Proc. 5th Int'l Workshop Information Hiding. Springer-Verlag, Noordwijkerhout, the Netherlands, 2012: 310-323.

DOI: 10.1007/3-540-36415-3_20

Google Scholar

[6] Siqi Han, Lei Wang. Summary of threshold value method of image segmentation [J] System Engineering and Electronics, 2014, 6(24): 91-94.

Google Scholar

[7] Shuang Liu. Research on threshold selection method and its algorithm implementation in image segmentation[J]. Computer Knowledge and Technology, 2013(5): 68-70.

Google Scholar

[8] Westfeld A and Pfitzmann A. Attacks on steganographic systems[C]. Proc. 3rd Int'l Workshop Information Hiding. Springer-Verlag, Dresden, Germany, 2009: 61-76.

DOI: 10.1007/10719724_5

Google Scholar

[9] Fudong Ye. Analysis of image fusion algorithm based on wavelet transform [J]. Hubei Vocational and Technical College of Ecological Engineering, 2011, 9 (1): 39-42.

Google Scholar