• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.887-890
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• 2012

Image recognition is one of the most important research directions of pattern recognition. Image based road automatic identification technology is widely used in current society, the intelligence has become the trend of the times. This paper studied the image segmentation algorithm theory and its application in road signs recognition system. With the help of image processing technique, respectively, on road signs automatic recognition algorithm of three main parts, namely, image segmentation, character segmentation, image and character recognition, made a systematic study and algorithm. The experimental results show that: the image segmentation algorithm to establish road signs recognition model, can make effective use of smart phone system and application.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.806-816
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• 2009

Character recognition system consists of four step; text localization, text segmentation, character segmentation, and recognition. The character segmentation is very important and difficult because of noise, illumination, and so on. For high recognition rates of the system, it is necessary to take good performance of character segmentation algorithm. Many algorithms for character segmentation have been developed up to now, and many people have been recently making researches in segmentation of touching or overlapping character. Most of algorithms cannot apply to the text regions of management number marked on the slab in steel image, because the text regions are irregular such as touching character by strong illumination and by trouble of nozzle in marking machine, and loss of character. It is difficult to gain high success rate in various cases. This paper describes a new algorithm of character segmentation to recognize slab management number marked on the slab in the steel image. It is very important that pre-processing step is to convert gray image to binary image without loss of character and touching character. In this binary image, non-touching characters are simply separated by using vertical projection profile. For separating touching characters, after we use combined profile to find candidate points of boundary, decide real character boundary by using method based on recognition. In recognition step, we remove noise of character images, then recognize respective character images. In this paper, the proposed algorithm is effective for character segmentation and recognition of various text regions on the slab in steel image.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.427-430
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• 1995

This paper proposes a new image processing algorithm to recognize korean documents. It take out the region of syllable area from input character image, then it makes recognition of a consonant and a vowel in the character. A precision segmentation is very important to recognize the input character. The input image has 8-bit gray scaled resolution. Not only the shape but also vertical and horizontal lines dispersion graph are used for segmentation. Theresult shows a higher accuracy of character segmentation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.233-237
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• 2013

Image recognition is an important research area of pattern recognition. This paper studies that the image segmentation algorithm theory and its application in road signs recognition system. In this paper We studied a systematic study for road signs and we have made the recognition algorithm. This paper is divided in image segmentation part and image recognition part for the road signs recognition. The experimental results show that the road signs recognition model can make effective use in smart phone system, and the model can be used in many other fields.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.221-228
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• 2018

Skin-color information is not sufficient for palmprint segmentation in complex scenes, including mobile environments. Traditional active shape model (ASM) combines gray information and shape information, but its performance is not good in complex scenes. An improved ASM method is developed for palmprint segmentation, in which Perux method normalizes the shape of the palm. Then the shape model of the palm is calculated with principal component analysis. Finally, the color likelihood degree is used to replace the gray information for target fitting. The improved ASM method reduces the complexity, while improves the accuracy and robustness.

• ETRI Journal
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• v.39 no.2
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• pp.163-172
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• 2017

A high performance license plate recognition system (LPRS) is proposed in this work. The proposed LPRS is composed of the following three main stages: (i) plate region determination, (ii) character segmentation, and (iii) character recognition. During the plate region determination stage, the image is enhanced by image processing algorithms to increase system performance. The rectangular license plate region is obtained using edge-based image processing methods on the binarized image. With the help of skew correction, the plate region is prepared for the character segmentation stage. Characters are separated from each other using vertical projections on the plate region. Segmented characters are prepared for the character recognition stage by a thinning process. At the character recognition stage, a three-layer feedforward artificial neural network using a backpropagation learning algorithm is constructed and the characters are determined.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.536-537
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• 2018

A goal of this paper is doing fine grained recognition of breed of animal from pet images. Research about fine grained recognition from images is continuously developing, but it is not for animal object recognition because they have polymorphism. This paper proposes method of higher animal object recognition using Grab-cut algorithm for object segmentation and Fisher Vector for image encoding.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1391-1394
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• 1997

This paper proposes a new image processing algorithm to recognize korean documents. It take out the region of text area form input image, then it makes esgmentation of lines, words and characters in the text. A precision segmentation is very important to recognize the input document. The input image has 8-bit gray scaled resolution. Not only the histogram but also brightness dispersion graph are used for segmentation. The result shows a higher accuracy of document recognition.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.1
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• pp.39-44
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• 2002

In this paper, implementation mode image segmentation method for separate image is presented. The method of segmentation image in conventional method, the error are generated by the threshold values. To improve these problem for segmentation image, the calculation of weighting factor using brightness distribution by histogram of stored images are proposed. For safe image of object and laser image, the computed weighting factor is set to the threshold value. Therefore the image erosion and spread are improved, the correct and reliable informations can be measured. In this paper, the system of 3-D extracting information using the proposed algorithm can be applied to manufactory automation, building automation, security guard system, and detecting information system for all of the industry areas.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.376-381
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• 1992

This paper presents an expert system for the segmentation of a 2.5-D image. The results of two segmentation approaches, edge-based and region-based, are combined to produce a consistent and reliable segmentation. Rich information embedded in the 2.5-D image is utilized to obtain a view independent surface patch description of the image, which can facilitate object recognition considerably.