• Title/Summary/Keyword: Character Matching

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A Stroke Matching Method for the Off-line Recognition of Handprinted Hangul (필기체 한글의 오프라인 인식을 위한 획 정합 방법)

  • 김기철;김영식;이성환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.6
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    • pp.76-85
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    • 1993
  • In this paper, we propose a stroke matching method for the off-line recognition of handprinted Hangul. In this method, the preprocessing steps such as position normalization, contour tracing and thinning are carried out first. Then, after extracting features such as the firection component distribution of contour, the direction component distribution of skeleton, and the distribution of structural feature points, strokes are extracted and matched based on the midpont distribution of the direction and the length of each stroke. In order to reduce the recognition time, a preliminary classification based on the direction component distribution features of the contour is performed. In order to domonstrate the performance of the proposed method, experiments with 520 most frequently used Hangul were performed, and 90.7% of correct recognition rate and 0.46second of recognition time per one character has been obtained. This results reveal that the proposed method can absorb effectively the noise in input character and the variations of stroke slant.

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Character Matching Using a Hausdorff Distance (Hausdorff 거리를 이용한 문자 매칭)

  • Kim, Kyeongtaek;Kyung, Ji Hun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.2
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    • pp.56-62
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    • 2015
  • The Hausdorff distance is commonly used as a similarity measure between two-dimensional binary images. Since the document images may be contaminated by a variety of noise sources during transmission, scanning or conversion to digital form, the measure should be robust to the noise. Original Hausdorff distance has been known to be sensitive to outliers. Transforming the given image to grayscale image is one of methods to deal with the noises. In this paper, we propose a Hausdorff distance applied to grayscale images. The proposed method is tested with synthetic images with various levels of noises and compared with other methods to show its robustness.

A Geocoding Method on Character Matching in Indoor Spaces (실내 공간에서의 문자매칭 기반 지오코딩 기법)

  • Lee, Kang-Jae;Lee, Jiyeong
    • Spatial Information Research
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    • v.21 no.1
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    • pp.87-100
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    • 2013
  • Recently, the use of locational information is growing rapidly. GPS technology has been adopted generally for obtaining locational information in outdoor spaces. In the other hand, the researches on indoor positioning have been carried out applying WLAN, RFID or Bluetooth technology because of the multi-path interference of GPS signal caused by the physical obstacles such as walls or columns in buildings. However, such technologies for indoor positioning cost too much to build sensing infrastructure and compute-intensive processes are involved. Furthermore, the accuracy of location estimation is variable caused by interior structures in buildings. In this study, to make up for the limitations, descriptive data such as phone number, unique room numbers, or business names readily available in mixed-use buildings is used for extracting location information. Furthermore, during the process, a geocoding method using character matching is applied to this study enabling prompt location estimation and sublating the fluctuation of accuracy caused by interior structures. Based on the proposed method in this study, an architecture is designed, and three-dimensional viewer program is developed for the implementation of this study. Also, this research is quantitatively analyzed through match rate and processing time of proposed method.

Recognition of License Plate with Brightness and Tone of Color Data (명암과 색상 정보를 이용한 번호판 인식)

  • Lee, Seung-Su;Lee, Kee-Seong
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.528-531
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    • 2003
  • Recognition of licence plate becomes a key issue to many traffic related application such as road traffic monitoring or parking lots access control. In this paper, the brightness, YIQ and HSI methods were used to locate a license. After the characters in license plate were extracted, template matching method was applied for character recognitions. To test the performance of the proposed algorithm, images of seventy vehicle were tested. The success rates for license plate and character recognition were approximately 99%, and 96%, respectively

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A Study on Character Recognition using HMM and the Mason's Theorem

  • Lee Sang-kyu;Hur Jung-youn
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.259-262
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    • 2004
  • In most of the character recognition systems, the method of template matching or statistical method using hidden Markov model is used to extract and recognize feature shapes. In this paper, we used modified chain-code which has 8-directions but 4-codes, and made the chain-code of hand-written character, after that, converted it into transition chain-code by applying to HMM(Hidden Markov Model). The transition chain code by HMM is analyzed as signal flow graph by Mason's theory which is generally used to calculate forward gain at automatic control system. If the specific forward gain and feedback gain is properly set, the forward gain of transition chain-code using Mason's theory can be distinguished depending on each object for recognition. This data of the gain is reorganized as tree structure, hence making it possible to distinguish different hand-written characters. With this method, $91\%$ recognition rate was acquired.

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Implementation of An On-Line Continuous Recognition System for Cursive Handwriting (자소간의 흘림을 허용하는 연속형 온라인 필기 인식 시스템의 구현)

  • 권오성;권영빈
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.9
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    • pp.166-177
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    • 1994
  • In this paper, an implemenation of on-line continuous recognizer for cursive Hangul handwriting is explained. For the Hangul recognition system, we propose a high speed string matching. The editing process in our proposed string matching is accomplished by single editing path. And the matching results are stored in a heap structure and we decide the user comfortibility of unceasing writing during recognition owing to the high speed matching. In the experimental result, a recongition rate of 86.36% at 1.75 second/character over 21,076 characters collected from 50 persons are abtained. And it is shown that the proposed recognition system is operated properly for the on-line recognition for cursive handwring between graphemes.

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DNA Inspired CVD Diagnostic Hardware Architecture (DNA 특성을 모방한 심혈관질환 진단용 하드웨어)

  • Kwon, Oh-Hyuk;Kim, Joo-Kyung;Ha, Jung-Woo;Park, Jea-Hyun;Chung, Duck-Jin;Lee, Chong-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.2
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    • pp.320-326
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    • 2008
  • In this paper, we propose a new algorithm emulating the DNA characteristics for noise-tolerant pattern matching problem on digital system. The digital pattern matching becomes core technology in various fields, such as, robot vision, remote sensing, character recognition, and medical diagnosis in particular. As the properties of natural DNA strands allow hybridization with a certain portion of incompatible base pairs, DNA-inspired data structure and computation technique can be adopted to bio-signal pattern classification problems which often contain imprecise data patterns. The key feature of noise-tolerance of DNA computing comes from control of reaction temperature. Our hardware system mimics such property to diagnose cardiovascular disease and results superior classification performance over existing supervised learning pattern matching algorithms. The hardware design employing parallel architecture is also very efficient in time and area.

Research on Effective Feature Vector Configuration for Motion Matching in Locomotive Motion Generation (보행 동작 생성을 위한 모션 매칭의 효과적인 특징 벡터 설정에 관한 연구)

  • Sura Kim;Sang Il Park
    • Journal of the Korea Computer Graphics Society
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    • v.29 no.3
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    • pp.159-166
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    • 2023
  • This paper investigates effective methods for implementing motion matching, which is actively used in real-time motion generation applications. The success of motion matching heavily hinges on its simple definition of a feature vector, yet this very definition can introduce significant variance in the outcomes. Our research focuses on identifying the optimal combination of feature vectors that effectively generates desired trajectories in locomotion generation. To this end, we experimented with a range of feature vector combinations and performed an in-depth error analysis to evaluate the results.

Precise Detection of Car License Plates by Locating Main Characters

  • Lee, Dae-Ho;Choi, Jin-Hyuk
    • Journal of the Optical Society of Korea
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    • v.14 no.4
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    • pp.376-382
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    • 2010
  • We propose a novel method to precisely detect car license plates by locating main characters, which are printed with large font size. The regions of the main characters are directly detected without detecting the plate region boundaries, so that license regions can be detected more precisely than by other existing methods. To generate a binary image, multiple thresholds are applied, and segmented regions are selected from multiple binarized images by a criterion of size and compactness. We do not employ any character matching methods, so that many candidates for main character groups are detected; thus, we use a neural network to reject non-main character groups from the candidates. The relation of the character regions and the intensity statistics are used as the input to the neural network for classification. The detection performance has been investigated on real images captured under various illumination conditions for 1000 vehicles. 980 plates were correctly detected, and almost all non-detected plates were so stained that their characters could not be isolated for character recognition. In addition, the processing time is fast enough for a commercial automatic license plate recognition system. Therefore, the proposed method can be used for recognition systems with high performance and fast processing.

An Adaptive Multi-Level Thresholding and Dynamic Matching Unit Selection for IC Package Marking Inspection (IC 패키지 마킹검사를 위한 적응적 다단계 이진화와 정합단위의 동적 선택)

  • Kim, Min-Ki
    • The KIPS Transactions:PartB
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    • v.9B no.2
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    • pp.245-254
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    • 2002
  • IC package marking inspection system using machine vision locates and identifies the target elements from input image, and decides the quality of marking by comparing the extracted target elements with the standard patterns. This paper proposes an adaptive multi-level thresholding (AMLT) method which is suitable for a series of operations such as locating the target IC package, extracting the characters, and detecting the Pinl dimple. It also proposes a dynamic matching unit selection (DMUS) method which is robust to noises as well as effective to catch out the local marking errors. The main idea of the AMLT method is to restrict the inputs of Otsu's thresholding algorithm within a specified area and a partial range of gray values. Doing so, it can adapt to the specific domain. The DMUS method dynamically selects the matching unit according to the result of character extraction and layout analysis. Therefore, in spite of the various erroneous situation occurred in the process of character extraction and layout analysis, it can select minimal matching unit in any environment. In an experiment with 280 IC package images of eight types, the correct extracting rate of IC package and Pinl dimple was 100% and the correct decision rate of marking quality was 98.8%. This result shows that the proposed methods are effective to IC package marking inspection.