Browsing by Author "Babatunde, R. S., and Ajao, J. F. (2019)"

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    A Comparative analysis of Texture feature and 3D colour Histogram for Content Based Image Retrieval.
    (U6+ Consortium of African Universities Proceedings. Maiden Edition on Harnessing African Potentials for Sustainable Development, Calabar, Nigeria., 2019-09-15) Babatunde, R. S., and Ajao, J. F. (2019)
    The visual content of an image can be used to search for similar images based on user interest from a large database, in the art known as Content Based Image Retrieval (CBIR). In CBIR systems, the user presents a query image to the system, the system obtains the feature vector, which is compared with certain image features of the images in the database. The adequacy of the feature vectors extracted for the retrieval of appropriate and exact image from the database is an open issue which calls for continual research and attention. This work involved the retrieval of similar images based on the content of the image by comparing the feature vectors of the queried image and those of the image database using Mahalanobis distance measure. Textural feature vectors of the images were obtained using local binary pattern and 3D colour histogram feature vectors were also extracted. The performances of these two different feature vectors were compared based on the distance metrics to determine their suitability. The similar images in the database are displayed along with their similarity distance value, in which the minimum distance is a metric for the matched images. The CBIR system was implemented using a locally acquired database of over 600 different images. Various images were used to query the CBIR system, which was able to successfully output similar images. The simulation result obtained revealed that textural feature vectors are more adequate in terms of speed and accuracy in content-based image retrieval than 3D colour histogram based on the images used in the experiment.