期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2021
卷号：12
期号：7
DOI：10.14569/IJACSA.2021.0120776
语种：English
出版社：Science and Information Society (SAI)
摘要：Image Retrieval Systems (IRSs) are applications that allow one to retrieve images saved at any location on a network. Most IRSs make use of reverse lookup to find images stored on the network based on image properties such as size, filename, title, color, texture, shape, and description. This paper provides a technique for obtaining full image document given that the user has some portions of the document under search. To demonstrate the reliability of the proposed technique, we designed a system to implement the algorithm. A combination of Optical Character Recognition (OCR) engine and an improved text-matching algorithm was used in the system implementation. The Tesseract OCR engine and Levenshtein Algorithm was integrated to perform the image search. The extracted text is compared to the text stored in the database. For example, a query result is returned when a significant ratio of 0.15 and above is obtained. The results showed a 100% successful retrieval of the appropriate file base on the match even when partial query images were submitted.
关键词：Image Retrieval Systems; image processing; Optical Character Recognition (OCR); text matching algorithm; Tesseract OCR engine; Levenshtein Algorithm
