An Efficient Approach towards Satellite Image Retrieval using Semantic Mining with Hashing
Linda Mary John and Kiran A Bhandari. An Efficient Approach towards Satellite Image Retrieval using Semantic Mining with Hashing. International Journal of Applied Information Systems 11(3):50-54, August 2016. URL, DOI BibTeX
@article{10.5120/ijais2016451592, author = "Linda Mary John and Kiran A. Bhandari", title = "An Efficient Approach towards Satellite Image Retrieval using Semantic Mining with Hashing", journal = "International Journal of Applied Information Systems", issue_date = "August 2016", volume = 11, number = 3, month = "Aug", year = 2016, issn = "2249-0868", pages = "50-54", numpages = 5, url = "http://www.ijais.org/archives/volume11/number3/931-2016451592", doi = "10.5120/ijais2016451592", publisher = "Foundation of Computer Science (FCS), NY, USA", address = "New York, USA" }
Abstract
Satellite images have gained a wide popularity in the field of content-based image retrieval. A massive amount of these images are collected every year due to the high availability of satellites and computer technologies. However, extracting user-specific content from these images still remains a primary concern due to the presence of semantic gap. This limits the capabilities of CBIR. Therefore, an effective and efficient method is required for image retrieval. This paper puts forward a semantic-based image retrieval approach along with the advantages of hashing for better feature extraction and precise retrieval. Hashing accelerates the quality of similarity search among images by generating unique image-hash codes .This approach also aims to scale down the problems related to semantic gap for better retrieval results.
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Keywords
Semantic mining, Hashing, Hash codes, Semantic gap, Feature extraction, Semantic-based image retrieval, Precision, Recall.