[1]ALIYA Batur,NURBIYA Yadikar,HORNISA Mamat,et al.Complex Uyghur document image matching and retrieval based on modified SURF feature[J].CAAI Transactions on Intelligent Systems,2019,14(2):296-305.[doi:10.11992/tis.201709014]
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Complex Uyghur document image matching and retrieval based on modified SURF feature

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 14 Number of periods: 2019 2 Page number: 296-305 Column: 学术论文—自然语言处理与理解 Public date: 2019-03-05
Title:
Complex Uyghur document image matching and retrieval based on modified SURF feature
Author(s):
ALIYA Batur1;  NURBIYA Yadikar1;  HORNISA Mamat1;  ALIMJAN Aysa2;  KURBAN Ubul1
1. School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China;
2. Network and information center, Xinjiang University, Xinjiang University, Urumqi 830046, China
Keywords:
complex document image; Uyghur document image; document image segmentation; feature extraction; SURF feature; FALNN bidirectional matching; KD-Tree+BBF matching; image retrieval
CLC:
TP391.1
DOI:
10.11992/tis.201709014
Abstract:
This study is aimed at the uncertainty and computational complexity of the clustering center in local image features retrieval based on the bag-of-words (BOW) model. A method to retrieve the measure of similarity degree from different kinds of distance and another method that requires using the matching point number as the basis of retrieval are proposed in this paper. In this method, the SURF feature is first modified to effectively reduce feature extraction complexity, and then FLANN (fast library for approximate nearest neighbors) bidirectional matching and KD-Tree + BBF matching are implemented for FAST + SURF features. Feature robustness is verified under different transformation conditions. Finally, all kinds of Uyghur document images that have been classified and sorted based on these two retrieval methods are retrieved. The results of the retrieval experiments indicate that the similarity degree measure retrieval based on distance is inferior to the retrieval based on matching number, and both of these two retrieval strategies can meet the requirements of fast and accurate searching.
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