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Archive Film Defect Detection Based on a Hidden Markov Model

Xiaosong Wang, Majid Mirmehdi, Archive Film Defect Detection Based on a Hidden Markov Model. Proceedings of the 10th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2009). May 2009. PDF, 652 Kbytes.

Abstract

We propose a novel statistical approach to detect defects in digitized archive film by using temporal information across a number of frames modeled with an HMM. The HMM is trained for normal observation sequences and then applied within a framework to detect defective pixels by examining each new observation sequence and its subformations via a leave-one-out process. We compare against state-of-the-art results to demonstrate that the proposed method achieves better detection rates, with fewer false alarms.

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