Citation

Sim, Kok Swee and Toa, Chean Khim and Lim, Zheng You and Lim, Kathy C. Y. (2022) Bezier-Exemplar Hybrid based Image Inpainting Method in Computerized Colorimetric Protein Estimation System. IAENG International Journal of Computer Science, 49 (2). pp. 1-6. ISSN 1819-9224

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Abstract

During the quality assurance process of latex gloves, the modified Lowry method is considered as one of the standard methods to determine the protein concentration for quality assurance. Nevertheless, this traditional method requires several tedious chemical processes, which results in time-consuming. To overcome this weakness, our previous work has implemented a new method based on image processing namely Computerized Colorimetric Protein Estimation Method (CCPE). This method provides fast and efficient in determining the protein concentration with an uncomplicated chemical test and the aid of computer vision technology. In the CCPE method, there will be a section where a scanner will be used to scan glove samples and convert samples into a digital image. Afterward, the digitalized glove sample image will go through computerized algorithms to estimate the protein concentration. However, during the scanning process, wrinkles on the image will affect the accuracy of the estimation results. Thus, this paper presents our implemented Bezier-exemplar Hybrid based Image Inpainting (BeHbII) method that is used to eliminate out the wrinkle of the image efficiently. The results shows that the inpainting method can restore the wrinkled image up to 99% similarity based on the unwrinkled original image of the same glove model and improve the accuracy of protein concentration detection up to 96%. This method does not limit to the latex glove imaging process but contributes to other imaging fields that face the wrinkles issue too.

Item Type:	Article
Uncontrolled Keywords:	Latex Glove, Image Processing, Inpainting, Wrinkles
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	22 Jul 2022 01:24
Last Modified:	24 Feb 2023 05:57
URII:	http://shdl.mmu.edu.my/id/eprint/10171

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