2013
DOI: 10.1109/tcsvt.2013.2269016
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Detection of Blotch and Scratch in Video Based on Video Decomposition

Abstract: In old video restoration, automatic detection of common defects, e.g., scratches and blotches, has always been emphasized. While prior thoughts mainly focus on detecting blotches and linear, vertical scratches separately, this paper contributes to a more generalized and challenging issue: simultaneous detection of blotches and complex scratches in video, with much less knowledge of them. We investigate the characteristics of blotches and scratches in space and time domain, and propose a novel detection method … Show more

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Cited by 18 publications
(6 citation statements)
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“…There are numerous algorithms aiming to enhance visibility of the degraded imagery, such as image and video denoising/inpainting [75][76][77][78][79], deblurring [80,81,162? ?…”
Section: B Poor Visibility Enhancementmentioning
confidence: 99%
“…There are numerous algorithms aiming to enhance visibility of the degraded imagery, such as image and video denoising/inpainting [75][76][77][78][79], deblurring [80,81,162? ?…”
Section: B Poor Visibility Enhancementmentioning
confidence: 99%
“…To detect blotch and line scratches, [25] experimented a detection method based on cartoon-texture decomposition in the space domain and content-defect separation in the time domain. The distinction between defect or not was handled temporally, using matrix decomposition in a low-rank matrix in addition to a sparse matrix representing the defects.…”
Section: Scratch and Blotch And Deep Learningmentioning
confidence: 99%
“…Convolutional neural networks (CNNs) [20] have brought unprecedented success in many computer vision tasks, including some recent works addressing fingerprint extraction and analysis [1,2]. On the other hand, fingerprint restoration and enhancement have been traditionally studied using classical example-based and regression methods [3,4,5,8] [6,10,11,17,18], the recent ECCV 2018 ChaLearn competition 3 has started to motivate researchers to develop deep learning algorithms that can restore fingerprint images that contain artifacts such as noise, scratches [7,9], etc. to improve the performance of subsequent operations like fingerprint verification that are typically applied to such images.…”
Section: Introductionmentioning
confidence: 99%