• Title/Summary/Keyword: 특징 히스토그램

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Extraction of Car License Plate Region Using Histogram Features of Edge Direction (에지 영상의 방향성분 히스토그램 특징을 이용한 자동차 번호판 영역 추출)

  • Kim, Woo-Tae;Lim, Kil-Taek
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.3
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    • pp.1-14
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    • 2009
  • In this paper, we propose a feature vector and its applying method which can be utilized for the extraction of the car license plate region. The proposed feature vector is extracted from direction code histogram of edge direction of gradient vector of image. The feature vector extracted is forwarded to the MLP classifier which identifies character and garbage and then the recognition of the numeral and the location of the license plate region are performed. The experimental results show that the proposed methods are properly applied to the identification of character and garbage, the rough location of license plate, and the recognition of numeral in license plate region.

e-Catalogue Image Retrieval Using Vectorial Combination of Color Edge (컬러에지의 벡터적 결합을 이용한 e-카탈로그 영상 검색)

  • Hwang, Yei-Seon;Park, Sang-Gun;Chun, Jun-Chul
    • The KIPS Transactions:PartB
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    • v.9B no.5
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    • pp.579-586
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    • 2002
  • The edge descriptor proposed by MPEG-7 standard is a representative approach for the contents-based image retrieval using the edge information. In the edge descriptor, the edge information is the edge histogram derived from a gray-level value image. This paper proposes a new method which extracts color edge information from color images and a new approach for the contents-based image retrieval based on the color edge histogram. The poposed method and technique are applied to image retrieval of the e-catalogue. For the evaluation, the results of image retrieval using the proposed approach are compared with those of image retrieval using the edge descriptor by MPEG-7 and the statistics shows the efficiency of the proposed method. The proposed color edge model is made by combining the R,G,B channel components vectorially and by characterizing the vector norm of the edge map. The color edge histogram using the direction of the color edge model is subsequently used for the contents-based image retrieval.

A Study on Skull & panorama Image recognition of feature exctraction using the Wavele Transform (웨이브렛 변환을 이용한 Skull & Panorama 영상 인식과 특징 추출에 관한 연구)

  • 문일남;김장형
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.113-117
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    • 2003
  • In this paper, have necessity of PACS (Picture Archiving and Communication System) at hospital but hereafter by economical problem PACS apply this to medical treatment image enhancing image quality applying histogram equalization for improvement of light and darkness after reconstruct because make image that pretreatment filtering has wild picture and is processed in wave lets dissolution and wave lets area using weight median filter because could not buy expensive equipment at hospital which introduction is difficulty do inversion and extracted characteristic.

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Reversible Image Watermarking with Differential Histogram Shifting and Error Prediction Compensation (차이값 히스토그램 쉬프팅과 오류 예측 보정을 이용한 가역 영상 워터마킹)

  • Yeo, Dong-Gyu;Lee, Hae-Yeoun;Kim, Byeong-Man;Kim, Kyung-Su
    • Journal of KIISE:Software and Applications
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    • v.37 no.6
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    • pp.417-429
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    • 2010
  • Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved and then enables to restore the original media from the marked one without any loss of media quality. This watermarking can be applied to quality-sensitive imaging such as medical imaging, military imaging, remote-sensing imaging, and precious artwork, where the original media should be preserved during image processing and analysis. In this paper, a reversible image watermarking technique that embeds message bits by modifying the differential histogram of adjacent pixels is presented. In order to satisfy both high embedding capacity and visual quality, the proposed technique exploits the fact that adjacent pixels in the image have highly spatial correlation. Also, we prevent overflow/underflow problem and salt-and-pepper artifacts by employing a predicted error compensation scheme. Through experiments using various test images, we prove that the presented technique provides perfect reversibility and high embedding capacity, while maintaining the induced-distortion low.

A Study on Improvement of Vision Inspector for T Type Welding nut auto Sorting System using a Masked Histogram Equalization (마스크 히스토그램 평준화를 이용한 T형 용접너트 자동 선별시스템의 비전검사기 성능개선에 관한 연구)

  • Hur, Tae-Won;Song, Han-Lim
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.9
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    • pp.353-361
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    • 2012
  • In this paper, we propose a improvement method of vision inspector for T type welding nut using an auto sorting system. We used edge and thread detection with histogram of image which is captured by machine vision camera. We also used a binary morphology operation for a detection of spot. A major problem in this vision inspector is abnormal operation caused by degradation of image acquired. These degradations caused by oil pollution on conveyer belt. For overcome this problem, we introduce a pre-processing using a masked histogram equalization on the image acquired. Histogram equalization is applied on masked region (nut part) for increase contrast. As a result, we can remove features caused by oil pollution on background and reduce a ratio of abnormal operation from 10.0 % to 0.2 %.

Global Contrast Enhancement Using Block based Local Contrast Improvement (블록기반 지역 명암대비 개선을 통한 전역 명암대비 향상 기법)

  • Kim, Kwang-Hyun;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.1
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    • pp.15-24
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    • 2008
  • This paper proposes a scheme of global image contrast enhancement using local contrast improvement. Methods of global image contrast enhancement redistribute the image gray level distribution using histogram equalization without considering image properties, and cause the result image to include image pixels with excessive brightness. On the other hand, methods of the block-based local image contrast enhancement have blocking artifacts and a problem of eliminating important image features during an image process to reduce them. In order to solve these problems, the proposed method executes the block-based histogram equalization on temporary images that an input image is divided into various fixed-size blocks. And then it performs the global contrast enhancement by applying the global histogram equalization functions to the original input image. Since the proposed method selects the best histogram equalization function from temporary images that are improved by the block-based local image contrast enhancement, it has the advantages of both the local and global image contrast enhancement approaches.

Music Identification Using Pitch Histogram and MFCC-VQ Dynamic Pattern (피치 히스토그램과 MFCC-VQ 동적 패턴을 사용한 음악 검색)

  • Park Chuleui;Park Mansoo;Kim Sungtak;Kim Hoirin
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.3
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    • pp.178-185
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    • 2005
  • This paper presents a new music identification method using probabilistic and dynamic characteristics of melody. The propo3ed method uses pitch and MFCC parameters as feature vectors for the characteristics of music notes and represents melody pattern by pitch histogram and temporal sequence of codeword indices. We also propose a new pattern matching method for the hybrid method. We have tested the proposed algorithm in small (drama OST) and broad (1.005 popular songs) search spaces. The experimental results on search areas of OST and 1,005 popular songs showed better performance of the proposed method over conventional methods. We achieved the performance improvement of average $9.9\%$ and $10.2\%$ in error reduction rate on each search area.

Enhanced Binarization Method using Fuzzy Membership Function (퍼지 소속 함수를 애용한 개선된 이진화 방법)

  • Kim Kwang Baek;Kim Young Ju
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.1 s.33
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    • pp.67-72
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    • 2005
  • Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

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Vision Inspection Method Development of Jig Plate Hole duster Using Contrast Enhancement (대비 향상을 사용한 지그 플레이트 홀 군집의 Vision 검사 방법 개발)

  • Park, Se-Hyuk;Han, Kwang-Hee;Kang, Su-Min;Huh, Kyung-Moo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.6
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    • pp.14-20
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    • 2009
  • The goal of image processing is to improve the visual appearance of images for human viewers. The histogram is an important tool which can be used as basic data of digital image processing. Therefore, to effectively manage a histogram in digital image processing is very important. Currently machine vision systems are used in many appearance inspection fields instead of inspection by human. However, the appearance inspection result by machine vision system is mainly influenced by illumination of workplace. In this paper, we propose a histogram transform method for improving accuracy of machine visual inspection. The enhancement effect of area feature is obtained by performing proposed histogram transformation in area that needs improvement The proposed algorithm is verified by appearance inspection of jig plate samples.

Object Oriented Retrieval using Shape Feature (형태 특징을 이용한 객체 중심 검색)

  • 정성호;김석현;황병곤
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2000.11a
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    • pp.391-395
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    • 2000
  • 본 논문에서는 영상을 구성하는 객체들이 가지고있는 형태 특징을 이용한 영상 검색 시스템을 제안한다. 형태 특징을 추출하기 위한 과정은 입력 영상에 Chain Code를 이용 경계면의 좌표와 길이를 구하는 과정, 경계면에 대한 무게 중심 추출과정으로 구성되고, 무게 중심으로부터 경계면 까지 거리의 합, 표준 편차, 장축/단축 비율 그리고 히스토그램 등을 특징 정보로 이용한다. 영상을 이루는 객체의 회전이나, 이동 등으로 인한 변화에 둔감하게 하고 형태 특징 중심으로 영상을 검색하도록 설계하였다. 실험 대상으로는 170개의 폐곡선을 이루는 이진 도형 영상에 대한 검색 실험을 실시하였다.

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