Abstract. Text detection in video images is a challenging research problem because of the poor spatial resolution and complex background, which may contain a variety of colors. An automated system for text detection in video images is presented. It makes use of four modules to implement a series of processes to extract text regions from video images. The first module, called the multistage pulse code modulation (MPCM) module, is used to locate potential text regions in color video images. It converts a video image to a coded image, with each pixel encoded by a priority code ranging from 7 down to 0 in accordance with its priority, and further produces a binary thresholded image, which segments potential text regions from the background. The second module, called the text region detection module, applies a sequence of spatial filters to remove noisy regions and eliminate regions that are unlikely to contain text. The third module, called the text box finding module, merges text regions and produces boxes that are likely to contain text. Finally, the fourth module, called the optical character recognition (OCR) module, eliminates the text boxes that produce no OCR output. An extensive set of experiments is conducted and demonstrates that the proposed system is effective in detecting text in a wide variety of video images.
Du et al. REF propose a methodology that uses MPCM (Multistage Pulse Code Modulation) to locate potential text regions in colour video images and then applies a sequence of spatial filters to remove noisy regions, merges text regions, produces boxes and finally eliminates the text boxes that produce no OCR output.
Automated system for text detection in individual video images
ICPR
Computer Science