AN EXTENSIVE REVIEW OF METRICS FOR EVALUATING IMAGE BINARIZATION ALGORITHMS

Giorgiana Violeta Vlasceanu (), Cristian Avatavului () and Costin-Anton Boiangiu ()
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Giorgiana Violeta Vlasceanu: University Politehnica of Bucharest, Romania
Costin-Anton Boiangiu: University Politehnica of Bucharest, Romania

Journal of Information Systems & Operations Management, 2023, vol. 17, issue 1, 200-222

Abstract: This comprehensive review paper delves into the essential metrics utilized for the evaluation of image binarization algorithms. Image binarization, a pivotal preprocessing step in many computer vision and image processing systems, poses significant challenges regarding the quality of output. Hence, a diverse range of evaluation metrics has been introduced, each bearing its strengths and limitations. This paper aims to elucidate the fundamental metrics such as Mean Squared Error (𠑀𠑆ð ¸), Peak Signal-to-Noise Ratio (ð ‘ƒð ‘†ð ‘ ð ‘…), F-measure, Pseudo F-measure, and Distance-Reciprocal Distortion Measure (ð ·ð ‘…ð ·), explicating their definitions, interpretations, advantages, and disadvantages. Furthermore, particular attention is given to the influential Document Image Binarization COntest (DIBCO) standards that have significantly shaped the field of image binarization evaluation. A comparative analysis of these metrics is performed, highlighting their effectiveness, accuracy, and suitability under diverse scenarios. This paper also identifies the existing limitations and proposes potential directions for future research in the realm of image binarization evaluation.

Date: 2023
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