• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.6
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• pp.929-936
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• 1990

This paper describes the method of the Korean character recognition by means of feature points extraction. Also, the preprocessing neural chip for noise elimination, smoothing, thinning and feature point extraction has been designs. The subpatterns were separated by means of advanced index algorithm using mask, and recognized by means of feature points classification. The separation of the Korean character subpatterns was abtained about 97%, and the recognition of the Korean characters was abtained about 95%. The preprocessing neural chip was simulated on SPICE and layouted by double CMOS 2\ulcorner design rule.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.965-967
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• 1995

One of the most difficult tasks in the process of automatic vehicle license plate recognition is the extraction of each character from within license plate region. In many cases, characters, especially serial numbers of plates are connected together due to noise and plate accessories. The recognition process may not be successful without extracting these characters effectively. This paper presents an algorithm to extract these connected characters very effectively. The algorithm utilizes mathematical morphology, connected component analysis, and gradient filters for character extraction. The paper also presents thorough experimental results as well as details of the algorithm.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.906-909
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• 2000

Conventional caption extraction methods use the difference between frames or color segmentation methods from the whole image. Because these methods depend heavily on heuristics, we should have a priori knowledge of the captions to be extracted. Also they are difficult to implement. In this paper, we propose a method that uses little heuristics and simplified algorithm. We use topographical features of characters to extract the character points and use KMST(Kruskal minimum spanning tree) to extract the candidate regions for captions. Character regions are determined by testing several conditions and verifying those candidate regions. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is 98.2%. And then we can see the results that caption area in complex images is well extracted.

• 전자공학회논문지 IE
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• v.46 no.3
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• pp.19-25
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• 2009

In this paper, I suggested the character recognition methods which are used the centroid method and included the spherical transform from the rectangle coordination for the character recognition system and obtained the results of the above 78.14% average differential ratio for the character features. The character feature extraction system using the spherical transform method is suggested in this paper, and the possibilities of the method which is get the invariant feature for the character transition using the centroid are suggested through the differential ratio results.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.102-110
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• 1992

In this paper, a new method of character recognition is proposed. It uses density information, in addition to positional and directional information generally used, to recognize a character. Four directional feature primitives are extracted from the thinning templates on the observation that the output of the templates have directional property in general. A simple and fast feature extraction scheme is possible. Features are organized from recursive nonary tree(N-tree) that corresponds to normalized character area. Each node of the N-tree has four directional features that are sum of the features of it's nine sub-nodes. Every feature primitive from the templates are added to the corresponding leaf and then summed to the upper nodes successively. Recognition can be accomplished by using appropriate feature level of N-tree. Also, effectiveness of each node's feature vector was tested by experiment. A method to implement the proposed feature vector organization algorithm into hardware is proposed as well. The third generation node, which is 4$\times$4, is used as a unit processing element to extract features, and it was implemented in hardware. As a result, we could observe that it is possible to extract feature vector for real-time processing.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.8-15
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• 1993

This paper describes a normalization of character which is contained in the character recognition process. Line and dot density is computed on input character image and then image mapping is executed into destination. Also recognition is processed using overlap-partitioning of character image and extraction of 4 directional feature primitives. The validity of proposed nonlinear normalization algorithm could be verified by increment of recognition rate.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.05a
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• pp.62-63
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• 2001

• Journal of the Korean Institute of Telematics and Electronics
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• v.13 no.1
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• pp.23-30
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• 1976

In this paper, a method is proposed for the recognition of hand-written Hangeul. This is peiformed by extraction of the concave structural segments by phase rotation. Character patterns can be decomposed into the fundamental concave structural segments which are also categorized into segment sects, and the closure and phase features of each segment in set is represented by logics. By rotating the logic pattern, the topological and phase features of segment are extracted for the reliable recognition of the character. It is also evaluated that this method applies to a wide variety of shape, position and declination of the character.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.93-100
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• 2007

In this paper, a novel approach based on wavelet transform is proposed to process the scraped character which is represented on digital image. The basis idea is that the scraped character is described by its textured neighborhood, and it is decomposed into multiresolution features at different levels with its background region. The image is first decomposed into sub bands by applying Daubechies wavelets. Character features are extracted from the low frequency sub-bands by partition, FCM clustering and area-based region process. High frequency ones are activated by applying local energy density over a moving mask. Features are synthesized in order to reconstruct the original image state through inverse wavelet transform Background region is eliminated and character is extracted. The experimental results demonstrate the effectiveness of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.31-37
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• 2001

License plate recognition system for an exclusive bus-lane is made of 5 core parts which are vehicle detection, image acquisition individual character extraction, character recognition and data transmission. Among them, the accuracy of license plate extraction can bring effect significantly to the accuracy of a whole system recognition rate also the more exact extraction of license plate is required in various weather and environment conditions. Therefore in this paper we propose a plat extraction algorithm that makes pyramid structure to reduced the extraction processing time binarizes plate's template region using adaptive thresholding extracts candidate region containing plate, and verifies a final region using plate character distribution characteristics among the candidates. Experimenal results were exactly extracted the license plate region by using proposed method to the image obtained in an exclusive bus-lane with various weather and environment conditions.