Improved Characters Feature Extraction and Matching Algorithm Based on SIFT

According to SIFT algorithm does not have the property of affine invariance, and the high complexity of time and space, it is difficult to apply to real-time image processing for batch image sequence, so an improved SIFT feature extraction algorithm was proposed in this paper. Firstly, the MSER algo...

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Main Authors: Jiang, Yueqiu (Author), Cheng, Yiguang (Author), Gao, Hongwei (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2014-01-01.
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LEADER 02294 am a22002893u 4500
001 ijeecs3010_1019
042 |a dc 
100 1 0 |a Jiang, Yueqiu  |e author 
100 1 0 |e contributor 
700 1 0 |a Cheng, Yiguang  |e author 
700 1 0 |a Gao, Hongwei  |e author 
245 0 0 |a Improved Characters Feature Extraction and Matching Algorithm Based on SIFT 
260 |b Institute of Advanced Engineering and Science,   |c 2014-01-01. 
520 |a According to SIFT algorithm does not have the property of affine invariance, and the high complexity of time and space, it is difficult to apply to real-time image processing for batch image sequence, so an improved SIFT feature extraction algorithm was proposed in this paper. Firstly, the MSER algorithm detected the maximally stable extremely regions instead of the DOG operator detected extreme point, increasing the stability of the characteristics, and reducing the number of the feature descriptor; Secondly, the circular feature region is divided into eight fan-shaped sub-region instead of 16 square sub-region of the traditional SIFT, and using Gaussian function weighted gradient information field to construct the new SIFT features descriptor. Compared with traditional SIFT algorithm, The experimental results showed that the algorithm not only has translational invariance, scale invariance and rotational invariance, but also has affine invariance and faster speed that meet the requirements of real-time image processing applications. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.4000 
540 |a Copyright (c) 2013 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc-nd/4.0 
546 |a eng 
690 |a MSER algorithm; Feature Extraction; Character Recognition; SIFT algorithm 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 12, No 1: January 2014; 334-343 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v12.i1 
787 0 |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3010/1019 
856 4 1 |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3010/1019  |z Get fulltext