Cheolkon Jung

Stroke Filter for Text Localization in Video Images

In this paper, we propose stroke filter for text localization in video images. First, we give the definition of text, which is based on the analysis of previous methods and intrinsic characteristics of text. Secondly, the definition is realized in the form of stroke filter, which is elaborately designed based on local region analysis. We also discuss the relationship between the proposed stroke filter and the other related filters. Furthermore, stroke filter can be implemented in a fast way without convolution operation. The effectiveness and efficiency of stroke filter is validated by extensive experiments on a challenging database.

Text segmentation based on stroke filter

Most existing methods of text segmentation in video images are not robust because they do not consider the intrinsic characteristics of text. In this paper, we propose a novel method of text segmentation based on stroke filter (SF). First, we give the definition of text, which is realized in the form of stroke filter based on local region analysis. Based on stroke filter response, text polarity determination and local region growing modules are performed successively. The effectiveness of our method is validated by experiments on a challenging database.

A video summarization method for basketball game

There have been various research efforts on automatic summarization of sports video. However, most previous works were based on event detection and thus cannot reflect the semantic importance of scenes and content of a game. In this paper, a summarization method for basketball video is presented. The proposed method keeps track of score changes of the game by reading the numbers on the score board. Analysis of the score variation yields a video summary that consists of semantically important and interesting scenes such as reversal or pursuit. Experimental results indicate that the proposed method can summarize basketball video with reasonable accuracy.