28 February 2018 Automatic luminous reflections detector using global threshold with increased luminosity contrast in images
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Abstract
The incidence of luminous reflections (LR) in captured images can interfere with the color of the affected regions. These regions tend to oversaturate, becoming whitish and, consequently, losing the original color information of the scene. Decision processes that employ images acquired from digital cameras can be impaired by the LR incidence. Such applications include real-time video surgeries, facial, and ocular recognition. This work proposes an algorithm called contrast enhancement of potential LR regions, which is a preprocessing to increase the contrast of potential LR regions, in order to improve the performance of automatic LR detectors. In addition, three automatic detectors were compared with and without the employment of our preprocessing method. The first one is a technique already consolidated in the literature called the Chang–Tseng threshold. We propose two automatic detectors called adapted histogram peak and global threshold. We employed four performance metrics to evaluate the detectors, namely, accuracy, precision, exactitude, and root mean square error. The exactitude metric is developed by this work. Thus, a manually defined reference model was created. The global threshold detector combined with our preprocessing method presented the best results, with an average exactitude rate of 82.47%.
© 2018 SPIE and IS&T
Ricardo Petri Silva, Ricardo Petri Silva, Gustavo Taiji Naozuka, Gustavo Taiji Naozuka, Saulo Martiello Mastelini, Saulo Martiello Mastelini, Alan Salvany Felinto, Alan Salvany Felinto, } "Automatic luminous reflections detector using global threshold with increased luminosity contrast in images," Journal of Electronic Imaging 27(1), 011009 (28 February 2018). https://doi.org/10.1117/1.JEI.27.1.011009 . Submission: Received: 29 September 2017; Accepted: 29 January 2018
Received: 29 September 2017; Accepted: 29 January 2018; Published: 28 February 2018
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