An Efficient Method for Text Detection in Video Based on Stroke Width Similarity

Autor:	Seungwook Cha, Seong Soo Chun, Hanjin Ryu, Sanghoon Sull, Viet Cuong Dinh
Rok vydání:	2007
Předmět:	Similarity (geometry) Computer science Structuring element business.industry Search engine indexing ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Value (computer science) Pattern recognition Edge detection Effective method Semantic memory False alarm Artificial intelligence business
Zdroj:	Computer Vision – ACCV 2007 ISBN: 9783540763857 ACCV (1)
DOI:	10.1007/978-3-540-76386-4_18
Popis:	Text appearing in video provides semantic knowledge and significant information for video indexing and retrieval system. This paper proposes an effective method for text detection in video based on the similarity in stroke width of text (which is defined as the distance between two edges of a stroke). From the observation that text regions can be characterized by a dominant fixed stroke width, edge detection with local adaptive thresholds is first devised to keep text- while reducing background-regions. Second, morphological dilation operator with adaptive structuring element size determined by stroke width value is exploited to roughly localize text regions. Finally, to reduce false alarm and refine text location, a new multi-frame refinement method is applied. Experimental results show that the proposed method is not only robust to different levels of background complexity, but also effective to different fonts (size, color) and languages of text.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::374a513cd45c2bfc2fcc12c3c15a60f3 https://doi.org/10.1007/978-3-540-76386-4_18 Zobrazit plný text záznamu