Image Retrieval Through Free-Form Query using Intelligent Text Processing
S. A. Angadi1, Hemavati C. Purad2

1S. A. Angadi, Department of Computer Science and Engineering, VTU, Belagavi, (Karnataka), India.
2Hemavati C. Purad, Department of Computer Science and Engineering, VTU, Belagavi, (Karnataka), India.
Manuscript received on 24 May 2023 | Revised Manuscript received on 26May 2023 | Manuscript Accepted on 15 June 2023 | Manuscript published on 30 June 2023 | PP: 40-50 | Volume-12 Issue-7, June 2023 | Retrieval Number: 100.1/ijitee.G96180612723 | DOI: 10.35940/ijitee.G9618.0612723

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Abstract: Image Retrieval is the process of retrieving images from the image/multimedia databases. Retrieval of images are carried out with various types of queries, free-form query is a text-query that consists of single or multiple keywords and/or concepts or descriptions of images with or without the inclusion of wild-card characters and/or punctuations. This work aims to handle image retrieval based on free-form text queries. Simple & complex queries of conceptual descriptions of images are explored and an intelligent processing system with free-form queries based on the Bag-of-Words model is modified and built for natural scene images and on Diverse Social Images using the Damerau-Levenshtein edit distance measure. The efficacy of the proposed system is evaluated by testing 1500 free-form text queries and has resulted in a recall accuracy of 91.3% on natural scene images (of Wang/Corel database) and 100% on Diverse Social Images (of DIV400 dataset). These results show that the system proposed has produced satisfactory performance compared to published results such as the harmonic mean of precision and recall (i.e. F1-Score) of 76.70% & 63.32% at retrieval of 20 images etc in reported works. 
Keywords: Free-text query; Damerau-Levenshtein edit distance; Bag-of-Words Model
Scope of the Article: Computer Science Applications