Automated blurred image region classification

Aneta Bera, Bartłomiej Sacharski, Dariusz Sychel

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Citation:

A. Bera, B. Sacharski, D. Sychel, "Automated blurred image region classification", Journal of Theoretical and Applied Computer Science, vol. 8, no. 2, pp. 37-47, 2014.

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Keywords:

feature extraction, FISH, GLCM, edge detection, DWT, GLM, MLP, backpropagation, regularization

Abstract:

In this paper authors present a simple method for recognizing blurred regions in the image. Proposed algorithm is based on 81 simple features - moments of histogram of image subbands, that were obtained during image decomposition, and ratio derived from gray level co-occurrence matrix (GLCM) are used. The method is compared with a different method, that is based on approaches found in literature. To increase the efficiency of algorithms, authors combined three solutions (edge-detection, gray level co-occurrence matrix and fast image sharpness). The aim of the research was to verify whether it is possible to use simpler methods of feature extraction to achieve similar, or even better, results.