• Title/Summary/Keyword: Contour Tracking algorithm

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Ship Design Visualization System base on Augmented Reality (증강현실 기반의 선박설계 시각화 시스템)

  • Park, Mi-Jeong;Yoo, Seung-Hyeok;Kim, Eung-Kon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.249-251
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    • 2012
  • Augmented Reality (AR) enables the enhanced realism and interaction by providing the overlaid digital information on the user's view of the physical world. In this paper, we propose an AR-based ship design visualization system for presenting ship 3D model in smart phones or table PCs. The proposed system compute corner points and feature points by contour finding method and harris corner detector, and build a ship-design drawing database. By using SURF algorithm, key feature points are extracted from ship-design drawing image which is obtained by mobile camera. Then ship-design drawing image is recognized by matching the feature points stored in DB and extracted key feature points. 3D ship structures are visualized by overlaying the ship-design drawing image on the smart phone or table PC's screen. Compared to conventional 2D ship-design, proposed system helps to easily understand the structures of the ship and reduce the business design period. Thus, Enhanced competitiveness of business is expected.

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Recognition of Passports using Enhanced Neural Networks and Photo Authentication (개선된 신경망과 사진 인증을 이용한 여권 인식)

  • Kim Kwang-Baek;Park Hyun-Jung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.5
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    • pp.983-989
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    • 2006
  • Current emigration and immigration control inspects passports by the naked eye, registers them by manual input, and compares them with items of database. In this paper, we propose the method to recognize information codes of passports. The proposed passport recognition method extracts character-rows of information codes by applying sobel operator, horizontal smearing, and contour tracking algorithm. The extracted letter-row regions is binarized. After a CDM mask is applied to them in order to recover the individual codes, the individual codes are extracted by applying vertical smearing. The recognizing of individual codes is performed by the RBF network whose hidden layer is applied by ART 2 algorithm and whose learning between the hidden layer and the output layer is applied by a generalized delta learning method. After a photo region is extracted from the reference of the starting point of the extracted character-rows of information codes, that region is verified by the information of luminance, edge, and hue. The verified photo region is certified by the classified features by the ART 2 algorithm. The comparing experiment with real passport images confirmed the good performance of the proposed method.

Recognition of the Passport by Using Fuzzy Binarization and Enhanced Fuzzy Neural Networks

  • Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.603-607
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    • 2003
  • The judgment of forged passports plays an important role in the immigration control system, for which the automatic and accurate processing is required because of the rapid increase of travelers. So, as the preprocessing phase for the judgment of forged passports, this paper proposed the novel method for the recognition of passport based on the fuzzy binarization and the fuzzy RBF neural network newly proposed. first, for the extraction of individual codes being recognized, the paper extracts code sequence blocks including individual codes by applying the Sobel masking, the horizontal smearing and the contour tracking algorithm in turn to the passport image, binarizes the extracted blocks by using the fuzzy binarization based on the membership function of trapezoid type, and, as the last step, recovers and extracts individual codes from the binarized areas by applying the CDM masking and the vertical smearing. Next, the paper proposed the enhanced fuzzy RBF neural network that adapts the enhanced fuzzy ART network to the middle layer and applied to the recognition of individual codes. The results of the experiment for performance evaluation on the real passport images showed that the proposed method in the paper has the improved performance in the recognition of passport.

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Passport Recognition using Fuzzy Binarization and Enhanced Fuzzy RBF Network

  • Kim, Kwang-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.2
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    • pp.222-227
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    • 2004
  • Today, an automatic and accurate processing using computer is essential because of the rapid increase of travelers. The determination of forged passports plays an important role in the immigration control system. Hence, as the preprocessing phase for the determination of forged passports, this paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.

Image Emphasis by Histogram Reverse Tracking Alteration (히스토그램 분포도 역추적 변경에 의한 영상 강조)

  • 허진경;김향태
    • Journal of Intelligence and Information Systems
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    • v.10 no.1
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    • pp.1-11
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    • 2004
  • It is very important part of pre-processing for get better results by image processing that get emphasized image by processing of source image. Emphasized image is not only good looking image but clear and sharp image. Emphasized images are used very useful data at contour extraction and image recognition in image processing. It have different image recognition by how much represent a origin scene in row quality image. Present algorithms that get emphasized premier image do not get clear picture of degree that want in various kind of images and there is shortcoming that need much process times being proportional size of picture quality or accumulation degree of histogram. In this paper, we propose method to change distribution chart that pixels occupy in histogram as subsequentness in reflex of various kinds as well as that picture quality reflex method to emphasize so that is suitable in practical use purpose originally of premier. Proposed algorithm re-allot histogram distribution by reverse tracking histogram. Experimental images are same result and take less processing time than histogram equalization.

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Citrus sorting system with a color image boundary tracking (칼라 영상의 경계추적에 의한 윤곽선 인식이 적용된 귤 선별시스템)

  • Choi, Youn-Ho;Kwon, Woo-Hyen
    • Journal of Sensor Science and Technology
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    • v.11 no.2
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    • pp.93-101
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    • 2002
  • The quality of agricultural products is classified with various factors which are measured and determined by destructive and/or nondestructive method. NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. CCD color camera is used to measure external quality like color and a size of fruit. Today, nondestructive methods are widely researched. The quality and the grade of fruit loaded into a cup automatically and measured in real time by camera and NIR system is determined by infernal and external factors. This paper proposes modified boundary tracking algorithm which detects the contour of fruit's color image and make chain code faster than conventional method. The chain code helps compute a size of fruit image and find multiple loading of a fruit in single cup or fruit between two cups. The designed classification system sorts a citrus at speed of 8 fruit/s, with evaluating a brix, an acidity and a size grade.

Isosurface Component Tracking and Visualization in Time-Varying Volumetric Data (시변 볼륨 데이터에서의 등위면 콤포넌트 추적 및 시각화)

  • Sohn, Bong-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.225-231
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    • 2009
  • This paper describes a new algorithm to compute and track the deformation of an isosurface component defined in a time-varying volumetric data. Isosurface visualization is one of the most common method for effective visualization of volumetric data. However, most isosurface visualization algorithms have been developed for static volumetric data. As imaging and simulation techniques are developed, large time-varying volumetric data are increasingly generated. Hence, development of time-varying isosurface visualization that utilizes dynamic properties of time-varying data becomes necessary. First, we define temporal correspondence between isosurface components of two consecutive timesteps. Based on the definition, we perform an algorithm that tracks the deformation of an isosurface component that can be selected using the Contour Tree. By repeating this process for entire timesteps, we can effectively visualize the time-varying data by displaying the dynamic deformation of the selected isosurface component.

Character Extraction of Car License Plates using RGB Color Information and Fuzzy Binarization (RGB 컬러 정보와 퍼지 이진화를 이용한 차량 번호판의 개별 문자 추출)

  • 김광백;김문환;노영욱
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.1
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    • pp.80-87
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    • 2004
  • In this paper we proposed the novel feature extraction method that is able to extract the individual characters from the license plate area of the car image more precisely by using the RGB color information and the fuzzy binarization newly proposed. The proposed method, first, extracts from the original image the areas that the pixels with the colors around the green are concentrated on as the candidate areas of the license plate, and selects the area with the most intensive distribution of pixels with the white color among the candidate areas as the license plate area. Second the noises of the license plate area should be removed by using 34{\times}$3 Sobel masking, and the fuzzy binarization method are proposed and applied to the license plate area to generate the binarized image of the license plate area. Lastly, the application of the contour tracking algorithm to the binarized area extracts the individual characters from the license plate area. The experiment on a variety of the real car images showed that the proposed method generates the higher rate of success for character extraction than the previous methods.

Recognition of Resident Registration Card using ART2-based RBF Network and face Verification (ART2 기반 RBF 네트워크와 얼굴 인증을 이용한 주민등록증 인식)

  • Kim Kwang-Baek;Kim Young-Ju
    • Journal of Intelligence and Information Systems
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    • v.12 no.1
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    • pp.1-15
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    • 2006
  • In Korea, a resident registration card has various personal information such as a present address, a resident registration number, a face picture and a fingerprint. A plastic-type resident card currently used is easy to forge or alter and tricks of forgery grow to be high-degree as time goes on. So, whether a resident card is forged or not is difficult to judge by only an examination with the naked eye. This paper proposed an automatic recognition method of a resident card which recognizes a resident registration number by using a refined ART2-based RBF network newly proposed and authenticates a face picture by a template image matching method. The proposed method, first, extracts areas including a resident registration number and the date of issue from a resident card image by applying Sobel masking, median filtering and horizontal smearing operations to the image in turn. To improve the extraction of individual codes from extracted areas, the original image is binarized by using a high-frequency passing filter and CDM masking is applied to the binaried image fur making image information of individual codes better. Lastly, individual codes, which are targets of recognition, are extracted by applying 4-directional contour tracking algorithm to extracted areas in the binarized image. And this paper proposed a refined ART2-based RBF network to recognize individual codes, which applies ART2 as the loaming structure of the middle layer and dynamicaly adjusts a teaming rate in the teaming of the middle and the output layers by using a fuzzy control method to improve the performance of teaming. Also, for the precise judgement of forgey of a resident card, the proposed method supports a face authentication by using a face template database and a template image matching method. For performance evaluation of the proposed method, this paper maked metamorphoses of an original image of resident card such as a forgey of face picture, an addition of noise, variations of contrast variations of intensity and image blurring, and applied these images with original images to experiments. The results of experiment showed that the proposed method is excellent in the recognition of individual codes and the face authentication fur the automatic recognition of a resident card.

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