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Efficient Photo Image Retrieval System Based on Combination of Smart Sensing and Visual Descriptor


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Abstract

In this paper, we propose a novel efficient photo image retrieval method that automatically indexes for the searching of relevant images using a combination of geo-coded information and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates at the moment of capture, and the label leads to generating a geo-spatial index with three elements of latitude, longitude and image view direction. Then, content-based visual features are extracted, and combined with the geo-spatial information for indexing and retrieving the photo images. For user0027s querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to using a content-based ranking function. To evaluate the performance of the proposed algorithm, we assess the simulation performance in terms of average precision and F-score using a natural photo collection. Comparing the proposed approach to search using visual feature alone, an improvement of 20.8% (61.6201340.8) was observed. The experimental results show that the proposed method exhibited a slight enhancement of around 7.2% (61.6201354.4) in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful than using only visual feature for image retrieval.


Keywords


Pages

Total Pages: 12
Pages: 39-50

DOI
10.1080/10798587.2014.914274


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Published

Volume: 21
Issue: 1
Year: 2014

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Technical Report

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

TWO YEAR CITATIONS PER DOCUMENT (SJR DATA): 0.993 (2018)
SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."





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