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Using A Crop-Pest Ontology To Facilitate Image Retrieval

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Computers in Agriculture and Natural Resources, 4th World Congress Conference, Proceedings of the 24-26 July 2006 (Orlando, Florida USA) Publication Date 24 July 2006  701P0606.(doi:10.13031/2013.21932)
Authors:   Soonho Kim, Yunchul Jung, Howard W. Beck
Keywords:   ontology, crop pest ontology, image retrieval, graphical interface, ontology development, cataloging, software usability

Professionals in the agricultural field need a facility to retrieve photographic images related to their work, especially as the volume of such images continues to increase. However, current keyword-based image retrieval suffers from limitation of finding relevant images and helping users to find proper keywords. A new approach to image retrieval using an ontology addresses the limitations posed by the current keyword-based image retrieval, which is achieved by browsing images associated with an ontology. An ontology is a collection of concepts and relationships between them in a particular domain such as crops and related pests. The presented work used two hundred and ninety-one images for developing the ontologybased approach in the domain of crops and related pests. To enable browsing of images associated with the crop-pest ontology, images were indexed based on the ontology. The indexing process included analyses of each image caption based on grammatical structure and word meaning. A graphical interface was implemented for browsing images associated with concepts in the crop-pest ontology and was evaluated for finding relevant images and helping users to find proper keywords. The results of evaluation indicated that participants achieved high relevancy in the retrieval of images using the crop-pest ontology, comparing to the keyword-based image retrieval (p = .02). The results also indicated the strong possibility that the image retrieval using the crop-pest ontology can help users by transferring domain knowledge to them. The presented work showed the new approach of indexing and browsing images using the crop-pest ontology, which can help professionals retrieve images more easily and accurately in the agricultural field.

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