A new wavelet-median-moment based method for multi-oriented video text detection
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
An eigen value based approach for text detection in video
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Context-based indoor object detection as an aid to blind persons accessing unfamiliar environments
Proceedings of the international conference on Multimedia
Text extraction from scene images by character appearance and structure modeling
Computer Vision and Image Understanding
A phase-based approach for caption detection in videos
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
An approach for Bangla and Devanagari video text recognition
Proceedings of the 4th International Workshop on Multilingual OCR
Text extraction from natural scene image: A survey
Neurocomputing
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Both graphic text and scene text detection in video images with complex background and low resolution is still a challenging and interesting problem for researchers in the field of image processing and computer vision. In this paper, we present a novel technique for detecting both graphic text and scene text in video images by finding segments containing text in an input image and then using statistical features such as vertical and horizontal bars for edges in the segments for detecting true text blocks efficiently. To identify a segment containing text, heuristic rules are formed based on combination of filters and edge analysis. Furthermore, the same rules are extended to grow the boundaries of a candidate segment in order to include complete text in the input image. The experimental results of the proposed method show that the technique performs better than existing methods in terms of a number of metrics.