• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.73-81
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• 2007

This paper presents how to recognize the new-type vehicle license plate using multi-link recognizer after extract the features from characters. In order to assist this task, this paper proposed FE-MCBP to recognize each character that got through image preprocess, extract range of vehicle license plate and extract process of each character. FE-MCBP is the recognizer based on the features of the character, The recognizer is employed to identify the new-type vehicle licence plates which have both the hangul and the arabic numeral characters. And its recognition rate is improved 9.7 percent than the back propagation recognizer before. Also it makes use of extract of linear component and region coordinate generation technology to normalize a image of the tilted vehicle license plate. The recognition system of the new-type vehicle license plate make possible recognize a image of the tilted vehicle license plate when using this system. Also, this system can recognize the tilted or imperfect vehicle licence plates.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.125-132
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• 2012

In this paper, We proposes FE-SM/SONN for recognizing blurred and smeared skid mark image caused by sudden braking of a vehicle. In a blurred and smeared skid marks, tread pattern image is ambiguous. To improve recognition of such image, FE-SM/SONN reads skid marks utilizing Fuzzy Logic and distinguishing tread pattern SONN(Self Organization Neural Networks) recognizer. In order to substantiate this finding, 48 tire models and 144 skid marks were compared and overall recognition ratio was 89%. This study showed 13.51% improved recognition compared to existing back propagation recognizer, and 8.78% improvement than FE-MCBP. The expected effect of this research is achieving recognition of ambiguous images by extracting distinguishing features, and the finding concludes that even when tread pattern image is in grey scale, Fuzzy Logic enables the tread pattern recognizable.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.901-914
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• 2002

In this paper, We propose an efficient automatic caption detection and location method, caption recognition using FE-MCBP(Feature Extraction based Multichained BackPropagation) neural network for content based retrieval of video. Frames are selected at fixed time interval from video and key frames are selected by gray scale histogram method. for each key frames, segmentation is performed and caption lines are detected using line scan method. lastly each characters are separated. This research improves speed and efficiency by color segmentation using local maximum analysis method before line scanning. Caption detection is a first stage of multimedia database organization and detected captions are used as input of text recognition system. Recognized captions can be searched by content based retrieval method.