Prajakta Bastawade, Prof.Bharati Dixit
Text detection in natural scene images is important task for applications such as assistive navigation, auxiliary reading, image retrieval, scene understanding, etc.This paper explores a new framework to detect text strings in complex natural scene images which consists of two steps: A) image partition to find text character candidates based on local gradient features and color uniformity of character components and 2) character candidate grouping to detect text strings based on joint structural features of text characters.. In Boundary Clustering a new bigram-color-uniformity-based method is developed to model both text and attachment surface, and cluster edge pixels based on color pairs and spatial positions into boundary layers which is given as input tor the entire framework The given framework outperforms the state-of-the-art results on the public RRD which contains text only in horizontal orientation. and more effective on MSRA-TD500 which contains text in arbitrary orientations
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