Indexing and retrieval of malayalam news videos based on word image matching

Manjary P. Gangan, Anoop Kadan, Lajish V. L.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

News videos store a huge amount of information and are a source of historical archives. The amount of news data is growing rapidly and unpredictably, hence video indexing on news videos is a tedious job. Manual indexing even though effective, it is slow and most expensive for a massive volume of data. Content Based Indexing and Retrieval (CBIR) is a solution for this problem. Textual modality based on ticker texts is powerful enough to represent a news video since it highlights all the topics in a news bulletin. Searching and retrieval from Malayalam news videos are challenging due to the lack of effective tools for automatic content based indexing and retrieval from massive database analyzing the semantics of the news videos. The ticker texts are extracted automatically using mathematical morphology and region clustering and indexing and retrieval based on text or word image matching is implemented. Different methods like Dynamic Time Warping (DTW), Exclusive-OR (XOR), and Correlation are performed for word image matching. The features Discrete Cosine Transform (DCT) and Normalized Vertical Projection Profile (nvpp) are found to give better results.
Original languageEnglish
Title of host publication2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI): Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1103-1108
ISBN (Electronic)9781509063673
ISBN (Print)9781509063680
DOIs
Publication statusPublished - 04 Dec 2017
Externally publishedYes

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