TextFinder: An Automatic System to Detect and Recognize Text In Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Parsing: Unifying Segmentation, Detection, and Recognition
International Journal of Computer Vision
Detection of text region and segmentation from natural scene images
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Stroke-model-based character extraction from gray-level document images
IEEE Transactions on Image Processing
Automatic detection and recognition of signs from natural scenes
IEEE Transactions on Image Processing
Localizing and segmenting text in images and videos
IEEE Transactions on Circuits and Systems for Video Technology
Reliable algorithm for slab region localization using robust features
ISPRA'09 Proceedings of the 8th WSEAS international conference on Signal processing, robotics and automation
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This paper describes about the extraction of the text regions. In steel making process, it is very important to recognize the product management numbers because workers use it to tell quality and uses of slabs. Therefore automatic extraction of the slab management numbers is a prerequisite for automatic character segmentation and recognition system. In these days, many researchers have studied about the automatic text region detection from natural scenes, video frames, etc. However, these algorithms are not well suited for the steel plant environment. In this paper, the detail process of an improved edge-based horizontal text region detection method is described. Based on the above process, the selective binarization and the iterative character estimation are performed to find both side boundaries of the text region. Experimental results show that proposed method is robust and has higher detection rate.