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Generation of Visual Patterns from BoVW for Image Retrieval using modified Similarity Score FusionARULMOZHI, P. , ABIRAMI, M. |
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Author keywords
feature extraction, image fusion, image matching, image representation, supervised learning
References keywords
image(36), retrieval(19), visual(14), vision(13), recognition(12), pattern(11), cvpr(11), words(9), fusion(8), classification(8)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2020-05-31
Volume 20, Issue 2, Year 2020, On page(s): 101 - 112
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.02012
Web of Science Accession Number: 000537943500012
SCOPUS ID: 85087452294
Abstract
The Bag of Visual Words (BoVW) turns up to be an efficient method to represent images for Content Based Image Retrieval (CBIR). Despite their significant usage, the traditional BoVW method has low discriminative power and fails to provide spatial information, which increases the false positive images and reduces the precision values. To address the first issue, a novel way of identifying a set of visual words unique for each category, named as Visual Patterns (VP) is proposed. Also, the weight for the respective VPs and a new way of score calculations for similarity matching with the database images are proposed. Then, to address the second issue of enhancing the spatial information, late fusion of Gabor filter features along with VP is proposed. As a consequence, VP provides better discriminative power and Gabor filtering, taking advantage of its complementary clue, provides spatial information. Hence, it helps to reduce the false matches and improves the precision values. Experiments are carried out on the popular datasets, namely, Caltech 256, Oxford 5K and Inria Holidays datasets along with Flickr 1M dataset. The proposed method is compared with other BoVW based models and proved that the MAP value is improved 0.50 times from the basic BoVW model. |
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[1] A Novel Visual Indoor Positioning Method With Efficient Image Deblurring, Jia, Shuang, Ma, Lin, Yang, Songxiang, Qin, Danyang, IEEE Transactions on Mobile Computing, ISSN 1536-1233, Issue 7, Volume 22, 2023.
Digital Object Identifier: 10.1109/TMC.2022.3143502 [CrossRef]
[2] A Grid Feature-Point Selection Method for Large-Scale Street View Image Retrieval Based on Deep Local Features, Chu, Tianyou, Chen, Yumin, Huang, Liheng, Xu, Zhiqiang, Tan, Huangyuan, Remote Sensing, ISSN 2072-4292, Issue 23, Volume 12, 2020.
Digital Object Identifier: 10.3390/rs12233978 [CrossRef]
[3] Encoding hieroglyph segments to represent hieroglyphs following the bag of visual word model for retrieval, Pinilla-Buitrago, Laura Alejandra, Martínez-Trinidad, José Fco., Carrasco-Ochoa, Jesús Ariel, Expert Systems with Applications, ISSN 0957-4174, Issue , 2022.
Digital Object Identifier: 10.1016/j.eswa.2022.116983 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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