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    Towards Automatic Blotch Detection for Film Restoration by Comparison of Spatio-Temporal Neighbours


    Gaughran, Peter and Bergin, Susan and Reilly, Ronan (2010) Towards Automatic Blotch Detection for Film Restoration by Comparison of Spatio-Temporal Neighbours. In: AICS 2009: Artificial Intelligence and Cognitive Science. Lecture Notes in Computer Science book series (LNCS) (6206). Springer, pp. 114-123. ISBN 9783642170799

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    Abstract

    In this paper, a new method of blotch detection for digitised film sequences is proposed. Due to the aging of film stocks, their poor storage and/or repeated viewing, it is estimated that approximately 50% of all films produced prior to 1950 have either been destroyed or rendered unwatchable [1,2]. To prevent their complete destruction, original film reels must be scanned into digital format; however, any defects such as blotches will be retained. By combining a variation of a linear time, contour tracing technique with a simple temporal nearest neighbour algorithm, a preliminary detection system has been created. Using component labelling of dirt and sparkle the overall performance of the completed system, in terms of time and accuracy, will compare favourably to traditional motion compensated detection methods. This small study (based on 13 film sequences) represents a significant first step towards automatic blotch detection.

    Item Type: Book Section
    Additional Information: This is the preprint version of the paper: Gaughran P., Bergin S., Reilly R. (2010) Towards Automatic Blotch Detection for Film Restoration by Comparison of Spatio-Temporal Neighbours. In: Coyle L., Freyne J. (eds) Artificial Intelligence and Cognitive Science. AICS 2009. Lecture Notes in Computer Science, vol 6206. Springer, Berlin, Heidelberg
    Keywords: blotch; detection; film; restoration; machine vision;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8208
    Identification Number: 0.1007/978-3-642-17080-5_14
    Depositing User: Prof. Ronan Reilly
    Date Deposited: 11 May 2017 15:35
    Publisher: Springer
    Refereed: Yes
    URI:

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