Video Enhancement to Reduce Reflection and Darkness Caused by the Sunglasses using Fusion Algorithm
Divya A.K1, Bhagya H.K2, Ujwal U.J3
1Divya A K, Department of Computer Science & Engineering, KVG College of Engineering, Sullia, VTU Belagavi, Sullia (Karnataka), India.
2Dr. Bhagya H K, Department of Electronics and Communication Engineering, KVG College of Engineering Sullia, VTU Belagavi, Sullia (Karnataka), India.
3Dr. Ujwal U J, Department of Computer Science & Engineering, KVG College of Engineering, Sullia, VTU Belagavi, Sullia (Karnataka), India.
Manuscript received on 27 May 2024 | Revised Manuscript received on 05 June 2024 | Manuscript Accepted on 15 June 2024 | Manuscript published on 30 June 2024 | PP: 53-59 | Volume-13 Issue-5, June 2024 | Retrieval Number: 100.1/ijeat.D438913040424 | DOI: 10.35940/ijeat.D4389.13040424
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The enhancement of video of a person wearing sunglasses to reduce the reflection and darkness is a very challenging task in computer vision applications such as video surveillance—the existence of reflections and darkness caused by sunglasses results in intrusive images. The absence of a clear eye diminishes the visible quality of the complete face image. The eyes under sunglasses are not identifiable if the reflection and darkness from the sunglasses are present. This paper demonstrates the reduction of adverse artefacts, such as reflections and darkness in the eye region, caused by sunglasses. The system is implemented using the fusion algorithm, which consists of three modules: eyeglass tracking on face images, reduction of reflection, and reduction of darkness through image enhancement methods. The image enhancement method includes a colour balance algorithm and a histogram stretching algorithm. Firstly, an automatic glasses presence detection model, based on a Robust Local Binary Pattern, identifies the imaging process of the ocular region covered by the sunglasses. Secondly, a non-convex optimization scheme, guided by landmarks on the glasses, effectively reduces reflections through several iterations. The image enhancement method, incorporating Colour Balance and Histogram Stretching, is used to identify eye regions within sunglasses. The resulting regenerated eye regions within sunglasses exhibit increased brightness, subtle darkness, and minimized reflection. Objective evaluation metrics, such as peak signal-to-noise ratio, structural similarity index measure, and logarithmic mean square error, are used to assess the strength of the proposed system. Qualitative evaluations are conducted to demonstrate the sound quality of eyeglass face images with reduced reflection and darkness.
Keywords: Color balancing, Histogram Stretching, Non-convex Optimization, Robust Local Binary Pattern.
Scope of the Article: Image Analysis and Processing