• Title/Summary/Keyword: image analysis algorithm

Search Result 1,480, Processing Time 0.03 seconds

Detection of Lens Scan Alluk on LCD Surface (LCD 표면의 렌즈 스캔 얼룩 검출 기법)

  • Shin, Ji-Young;Kim, Jeong-Tae
    • The Transactions of the Korean Institute of Electrical Engineers D
    • /
    • v.55 no.12
    • /
    • pp.547-549
    • /
    • 2006
  • We have proposed a novel algorithm for detecting scan alluk on the surface of a TFT-LCD device that is generated by non-uniform exposure during fabrication. The scan alluk is known to have similar intensity values on paths that are determined by the shape of lens for light exposure. Based on the observation, the proposed algorithm inspects the uniformity on the paths using 1D projection image of 2D LCD image and 2D backprojection image of the 1D image. We have shown the usefullness of the proposed method by theoretical analysis and experimental results.

A Study on Implementation of Image Processing System for the Defect Inspection of polyethylene (팔레트의 불량검사를 위한 영상 처리 시스템 구현)

  • Kim, Kyoung-Min;Kang, Jong-Su;Park, Joong-Jo;Song, Myeong-Hyun
    • Proceedings of the KIEE Conference
    • /
    • 2001.07d
    • /
    • pp.2738-2740
    • /
    • 2001
  • This paper describes a study on implementation of image processing systems for the defect inspection of polyethylene. In order to detect the edge, the Robert filter is used. And we use to the labeling algorithm for feature extraction. Labeling the conected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. This algorithm is designed for the defect inspection of polyethylene.

  • PDF

Edge Enhanced Error Diffusion based on Local Average of Original Image (원영상의 로컬 평균을 이용한 경계강조 오차확산법)

  • Kang, Tae-Ha;Hwang, Byong-Won
    • The Transactions of the Korea Information Processing Society
    • /
    • v.7 no.8
    • /
    • pp.2565-2574
    • /
    • 2000
  • The error diffusion method is good for reproducing continuous image to binary image. However the reproduction of edge characteristic is weak in power spectrum analysis of display error. In this paper. we present an edge-enhanced error-diffusion method which include pre-processing algorithm for edge characteristic enhancement. Pre-processing algorithm consists of the difference value between current pixel and local average of original image and weighting function of pre-filter. First. it is obtained the difference value between current pixel and the local average of peripheral pixels(5x5) in original image. Second, weighting function of pre-filter is composed by function including absolute value and sign of difference value. The improved Error diffusion algorithm using pre-processing algorithm, present a good result visually which edge characteristic is enhanced. The performance of the proposed algorithm is compared with that of the conventional edge-enhanced error diffusion by measuring the RAPSD of display error, the egde correlation and the local average accordance.

  • PDF

IR Image Segmentation using GrabCut (GrabCut을 이용한 IR 영상 분할)

  • Lee, Hee-Yul;Lee, Eun-Young;Gu, Eun-Hye;Choi, Il;Choi, Byung-Jae;Ryu, Gang-Soo;Park, Kil-Houm
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.21 no.2
    • /
    • pp.260-267
    • /
    • 2011
  • This paper proposes a method for segmenting objects from the background in IR(Infrared) images based on GrabCut algorithm. The GrabCut algorithm needs the window encompassing the interesting known object. This procedure is processed by user. However, to apply it for object recognition problems in image sequences. the location of window should be determined automatically. For this, we adopted the Otsu' algorithm for segmenting the interesting but unknown objects in an image coarsely. After applying the Otsu' algorithm, the window is located automatically by blob analysis. The GrabCut algorithm needs the probability distributions of both the candidate object region and the background region surrounding closely the object for estimating the Gaussian mixture models(GMMs) of the object and the background. The probability distribution of the background is computed from the background window, which has the same number of pixels within the candidate object region. Experiments for various IR images show that the proposed method is proper to segment out the interesting object in IR image sequences. To evaluate performance of proposed segmentation method, we compare other segmentation methods.

Depth-based Correction of Side Scan Sonal Image Data and Segmentation for Seafloor Classification (수심을 고려한 사이드 스캔 소나 자료의 보정 및 해저면 분류를 위한 영상분할)

  • 서상일;김학일;이광훈;김대철
    • Korean Journal of Remote Sensing
    • /
    • v.13 no.2
    • /
    • pp.133-150
    • /
    • 1997
  • The purpose of this paper is to develop an algorithm of classification and interpretation of seafloor based on side scan sonar data. The algorithm consists of mosaicking of sonar data using navigation data, correction and compensation of the acouctic amplitude data considering the charateristics of the side scan sonar system, and segmentation of the seafloor using digital image processing techniques. The correction and compensation process is essential because there is usually difference in acoustic amplitudes from the same distance of the port-side and the starboard-side and the amplitudes become attenuated as the distance is increasing. In this paper, proposed is an algorithm of compensating the side scan sonar data, and its result is compared with the mosaicking result without any compensation. The algorithm considers the amplitude characteristics according to the tow-fish's depth as well as the attenuation trend of the side scan sonar along the beam positions. This paper also proposes an image segmentation algorithm based on the texture, where the criterion is the maximum occurence related with gray level. The preliminary experiment has been carried out with the side scan sonar data and its result is demonstrated.

Fire Detection Algorithm Based On Motion Information and Color Information Analysis (움직임 정보와 칼라정보 분석을 통한 화재검출 알고리즘)

  • Choi, Hong-seok;Moon, Kwang-seok;Kim, Jong-nam;Park, Seung-seob
    • Journal of Korea Multimedia Society
    • /
    • v.19 no.2
    • /
    • pp.180-188
    • /
    • 2016
  • In this paper, we propose a fire detection algorithm based on motion information and color information analysis. Conventional fire detection algorithms have as main problem the difficulty to detect fire due to external light, intensity, background image complexity, and little fire diffusion. So we propose a fire detection algorithm that accurate and fast. First, it analyzes the motion information in video data and then set the first candidate. Second, it determines this domain after analyzing the color and the domain. This algorithm assures a fast fire detection and a high accuracy compared with conventional fire detection algorithms. Our algorithm will be useful to real-time fire detection in real world.

Cell Counting Algorithm Using Radius Variation, Watershed and Distance Transform

  • Kim, Taehoon;Kim, Donggeun;Lee, Sangjoon
    • Journal of Information Processing Systems
    • /
    • v.16 no.1
    • /
    • pp.113-119
    • /
    • 2020
  • This study proposed the structure of the cluster's cell counting algorithm for cell analysis. The image required for cell count is taken under a microscope. At present, the cell counting algorithm is reported to have a problem of low accuracy of results due to uneven shape and size clusters. To solve these problems, the proposed algorithm has a feature of calculating the number of cells in a cluster by applying a radius change analysis to the existing distance conversion and watershed algorithm. Later, cell counting algorithms are expected to yield reliable results if applied to the required field.

Automatic Lipreading Based on Image Transform and HMM (이미지 변환과 HMM에 기반한 자동 립리딩)

  • 김진범;김진영
    • Proceedings of the IEEK Conference
    • /
    • 1999.11a
    • /
    • pp.585-588
    • /
    • 1999
  • This paper concentrates on an experimental results on visual only recognition tasks using an image transform approach and HMM based recognition system. There are two approaches for extracting features of lipreading, a lip contour based approach and an image transform based one. The latter obtains a compressed representation of the image pixel values that contain the speaker's mouth results in superior lipreading performance. In addition, PCA(Principal component analysis) is used for fast algorithm. Finally, HMM recognition tasks are compared with the another.

  • PDF

Implementation for Texture Imaging Algorithm based on GLCM/GLDV and Use Case Experiments with High Resolution Imagery

  • Jeon So Hee;Lee Kiwon;Kwon Byung-Doo
    • Proceedings of the KSRS Conference
    • /
    • 2004.10a
    • /
    • pp.626-629
    • /
    • 2004
  • Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program for GLCM algorithm is newly implemented in the MS Visual IDE environment. While, additional texture imaging modules based on GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV texture variables, it composed of six types of second order texture function in the several quantization levels of 2(binary image), 8, and 16: Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality, four directions are provided as $E-W(0^{\circ}),\;N-E(45^{\circ}),\;S-W(135^{\circ}),\;and\;N-S(90^{\circ}),$ and W-E direction is also considered in the negative direction of E- W direction. While, two direction modes are provided in this program: Omni-mode and Circular mode. Omni-mode is to compute all direction to avoid directionality problem, and circular direction is to compute texture variables by circular direction surrounding target pixel. At the second phase of this study, some examples with artificial image and actual satellite imagery are carried out to demonstrate effectiveness of texture imaging or to help texture image interpretation. As the reference, most previous studies related to texture image analysis have been used for the classification purpose, but this study aims at the creation and general uses of texture image for urban remote sensing.

  • PDF

Thermal Infrared Image Enhancement Method Based on Retinex (Retinex 처리에 기반한 적외선 열상 이미지의 화질 개선)

  • Lee, Won-Seok;Kim, Kyoung-Hee;Lee, Sang-Won
    • 전자공학회논문지 IE
    • /
    • v.48 no.2
    • /
    • pp.32-39
    • /
    • 2011
  • The output image of the uncooled thermal infrared camera is difficult the identification of target because of the limited dynamic range and the various noises. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, the image quality is insufficient when it is adopted to the narrow dynamic range image as the infrared image. In this paper, we propose the revised retinex algorithm to enhance the contrast of the infrared image. To improve the contrast enhancement performance, we designed the new dynamic range compression function instead of log function. To reduce the noise and compensate the loss of edge, we added the contrast compensation procedure in the MSR image generation process. According to the output picture comparing and numerical analysis, the proposed algorithm shows the better contrast enhancement performance and the more suitable method for the infrared image enhancement.