Comparative Study of OpenCV Inpainting Algorithms
Comparative Study of OpenCV Inpainting Algorithms
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image processing
Image Inpainting
Artificial Intelligence
Machine Learning

How to Cite

Preeti Chatterjee, Subhadeep Jana, & Souradeep Ghosh. (2021). Comparative Study of OpenCV Inpainting Algorithms. Global Journal of Computer Science and Technology, 21(G2), 27–37. Retrieved from


Digital image processing has been a significant and important part in the realm of computing science since its inception It entails the methods and techniques that are used to manipulate a digital image using a digital computer It is a type of signal processing in which the input and output maybe image or features characteristics associated with that image In this age of advanced technology digital image processing has its uses manifold some major fields being image restoration medical field computer vision color processing pattern recognition and video processing Image inpainting is one such important domain of image processing It is a form of image restoration and conservation This paper presents a comparative study of the various digital inpainting algorithms provided by Open CV a popular image processing library and also identifies the most effective inpainting algorithm on the basis of Peak Signal to Noise Ratio PSNR Structural Similarity Index SSIM and runtime metrics
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