Abstract
The use of medical images by medical practitioners has increased to an extent that computers have become a necessity in the image processing and analysis. This research investigates if the Edge density and Local Directional Pattern can be used to characterize medical images. The performance of the Edge density and Local Directional Pattern features is assessed by finding their accuracy to retrieve images of the same group from a database. The combination of the Edge density and Local Directional Pattern features has shown to produce good results in both, classification of medical images and image retrieval. For the classification using the nearest neighbor and 5-nearest neighbor techniques yielded 98.2 % and 99.6 % classification success rates respectively and 99.4 % for image retrieval. The results achieved in this research work are comparable to other approaches used in literature.
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Viriri, S. (2015). Characterization of Medical Images Using Edge Density and Local Directional Pattern (LDP). In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2015. Lecture Notes in Computer Science(), vol 9164. Springer, Cham. https://doi.org/10.1007/978-3-319-20801-5_43
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DOI: https://doi.org/10.1007/978-3-319-20801-5_43
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