SIFT Feature Extraction Algorithm for Image in DCT Domain

Image feature extraction is an important technology in image matching and retrieval. For the problem of high computational complexity of spatial domain image feature extraction using the SIFT algorithm, and by studying the relationship between DCT coefficient matrix and image, the paper designed the DCT coefficients reduced matrix of image and proposed the algorithm of SIFT feature extraction in DCT domain reduced image. Experiments showed that with the low loss of accuracy in image matching and retrieval, the method proposed can significantly improve the computational efficiency of feature extraction.

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Study of Fingerprint Image Feature Extraction Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.519-520.577 ◽

2014 ◽

Vol 519-520 ◽

pp. 577-580

Author(s):

Shuai Yuan ◽

Guo Yun Zhang ◽

Jian Hui Wu ◽

Long Yuan Guo

Keyword(s):

Feature Extraction ◽

Recognition System ◽

Fingerprint Recognition ◽

Image Feature ◽

Feature Points ◽

Orientation Field ◽

Fingerprint Image ◽

Image Feature Extraction ◽

Feature Extraction Algorithm ◽

Extraction Algorithm

Fingerprint image feature extraction is a critical step to fingerprint recognition system, which studies topological structure, mathematical model and extraction algorithm of fingerprint feature. This paper presents system design and realization of feature extraction algorithm for fingerprint image. On the basis of fingerprint skeleton image, feature points including ending points, bifurcation points and singular points are extracted at first. Then false feature points are detected and eliminated by the violent changes of ambient orientation field. True feature points are marked at last. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.

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Computer Image Feature Extraction Algorithm for Robot Visual Equipment

The Open Automation and Control Systems Journal ◽

10.2174/1874444301507011993 ◽

2015 ◽

Vol 7 (1) ◽

pp. 1993-2000

Author(s):

Wang Li

Keyword(s):

Feature Extraction ◽

Computer Image ◽

Image Feature ◽

Image Feature Extraction ◽

Feature Extraction Algorithm ◽

Extraction Algorithm

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SIFT Feature Extraction Algorithm for Image in DCT Domain

Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation ◽

10.2991/isccca.2013.64 ◽

2013 ◽

Cited By ~ 1

Author(s):

Zhen Wu ◽

Zhe Xu ◽

Rui-nian Zhang ◽

Shao-Mei Li

Keyword(s):

Feature Extraction ◽

Sift Feature ◽

Feature Extraction Algorithm ◽

Dct Domain ◽

Extraction Algorithm

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A modified welding image feature extraction algorithm for rotating arc narrow gap MAG welding

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-11-2014-0407 ◽

2015 ◽

Vol 42 (3) ◽

pp. 222-227 ◽

Cited By ~ 7

Author(s):

Wenhang Li ◽

Yunhong Ji ◽

Jing Wu ◽

Jiayou Wang

Keyword(s):

Feature Extraction ◽

Extraction Method ◽

Image Feature ◽

Mag Welding ◽

Narrow Gap ◽

Image Feature Extraction ◽

Content Type ◽

Feature Extraction Method ◽

Extraction Algorithm ◽

Welding Image

Purpose The purpose of this paper is to provide a modified welding image feature extraction algorithm for rotating arc narrow gap metal active-gas welding (MAG) welding, which is significant for improving the accuracy and reliability of the welding process. Design/methodology/approach An infrared charge-coupled device (CCD) camera was utilized to obtain the welding image by passive vision. The left/right arc position was used as a triggering signal to capture the image when the arc is approaching left/right sidewall. Comparing with the conventional method, the authors’ sidewall detection method reduces the interference from arc; the median filter removes the welding spatter; and the size of the arc area was verified to reduce the reflection from welding pool. In addition, the frame loss was also considered in the authors’ method. Findings The modified welding image feature extraction method improves the accuracy and reliability of sidewall edge and arc position detection. Practical implications The algorithm can be applied to welding seam tracking and penetration control in rotating or swing arc narrow gap welding. Originality/value The modified welding image feature extraction method is robust to typical interference and, thus, can improve the accuracy and reliability of the detection of sidewall edge and arc position.

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