• Title/Summary/Keyword: histogram distribution

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Image Search Using Interpolated Color Histograms (히스토그램 보간에 의한 영상 검색)

  • Lee, Hyo-Jong
    • The KIPS Transactions:PartB
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    • v.9B no.5
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    • pp.701-706
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    • 2002
  • A set of color features has been efficiently used to measure the similarity of given images. However, the size of the color features is too large to implement an indexing scheme effectively. In this paper a new method is proposed to retrieve similar images using an interpolated color histogram. The idea is similar to the already reported methods that use the distributions of color histograms. The new method is different in that simplified color histograms decide the similarity between a query image and target images. In order to represent the distribution of the color histograms, the best order of interpolated polynomial has been simulated. After a histogram distribution is represented in a polynomial form, only a few number of polynomial coefficients are indexed and stored in a database as a color descriptor. The new method has been applied to real images and achieved satisfactory results.

Selection Method of Multiple Threshold Based on Probability Distribution function Using Fuzzy Clustering (퍼지 클러스터링을 이용한 확률분포함수 기반의 다중문턱값 선정법)

  • Kim, Gyung-Bum;Chung, Sung-Chong
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.5 s.98
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    • pp.48-57
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    • 1999
  • Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

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A Study on response time measurement of FPD using statistical techniques of histogram

  • Lee, Yeun-Woo;Park, Gi-Chang;Lee, Sang-Dae
    • 한국정보디스플레이학회:학술대회논문집
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    • 2005.07a
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    • pp.506-510
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    • 2005
  • As FPD technology is getting improved, there are a lot of issues on signal processing and analysis, and its relative importance has been increasing day by day. In particular, response time sad in the evaluation item of FPD has been measured by oscilloscope. In this paper, we propose an effective measurement method of response time in FPD. The proposed method is to calculate the rising/ falling time by using statistical techniques of histogram and analyzing an energy distribution. Ultimately, the method has proved the utility and reliability by comparison of oscilloscope

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Abrupt Shot Change Detection Using the Bi-polarity Histogram Method (양극성 히스토그램 기법을 이용한 급격한 샷 전환점 검출)

  • 권성은;홍승범;백중환;도규봉
    • Proceedings of the IEEK Conference
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    • 2002.06a
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    • pp.259-262
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    • 2002
  • We propose a new algorithm to detect shot change, which is necessary in retrieval of video data. In order to solve the problems of abrupt brightness change and similar brightness between frames in the typical shot change methods, we propose the hi-polarity histogram method which takes into account the distribution and magnitude of brightness changes in consecutive frames. We evaluate our algorithm with compressed and uncompressed video data and demonstrate its improved performance.

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Development of surface defect inspection algorithms for cold mill strip using tree structure (트리 구조를 이용한 냉연 표면흠 검사 알고리듬 개발에 관한 연구)

  • Kim, Kyung-Min;Jung, Woo-Yong;Lee, Byung-Jin;Ryu, Gyung;Park, Gui-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.365-370
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    • 1997
  • In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

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Fuzzy Inference based Digital Color Management of Textile Dye Manufacturing (퍼지 추론에 기반 한 직물 염료 생산공정의 디지털 색상관리)

  • Kyungwon Jang;Jinhyun Kang;Jaemyoung Hwang;Taechon Ahn
    • Proceedings of the IEEK Conference
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    • 2003.07d
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    • pp.1533-1536
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    • 2003
  • In this paper, instead of conventional color management method that using spectrum analysis, a simplified color management scheme is proposed that is low-cost required method to reproduce the visual color perception of human. Proposed scheme uses computer color scanner to obtain a bit map image from dyed original color sample, and conducts pixel analysis by image histogram. From obtained image histogram, extract the color and RGB value from histogram that shows dominant pixel distribution of the sample image.

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Fingerprint Minutiae Matching Algorithm using Distance Histogram of Neighborhood

  • Sharma, Neeraj;Lee, Joon-Jae
    • Journal of Korea Multimedia Society
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    • v.10 no.12
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    • pp.1577-1584
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    • 2007
  • Fingerprint verification is being adopted widely to provide positive identification with a high degree of confidence in all practical areas. This popular usage requires reliable methods for matching of these patterns. To meet the latest expectations, the paper presents a pair wise distance histogram method for fingerprint matching. Here, we introduced a randomized algorithm which exploits pair wise distances between the pairs of minutiae, as a basic feature for match. The method undergoes two steps for completion i.e. first it performs the matching locally then global matching parameters are calculated in second step. The proposed method is robust to common problems that fingerprint matching faces, such as scaling, rotation, translational changes and missing points etc. The paper includes the test of algorithm on various randomly generated minutiae and real fingerprints as well. The results of the tests resemble qualities and utility of method in related field.

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A high performance disparity extraction algorithm using low resolution disparity histogram (저 해상도 변위 히스토그램을 이용한 고성능 변위정보 추출 알고리듬)

  • 김남규;이광도;김형곤;차균현
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.3
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    • pp.131-143
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    • 1998
  • This paper presents a high performance disparity extraction algorithm that generate a dense and accurate disparity map using low-resolution disparity histogram. Disparity distribution of background and object areas can besegmented from low-resolution disparity histogram. These information can be used to reduce the search area and search range of the high-resolution image resulting reliable disparity information in high speed. The computationally efficient matching pixel count(MPC) similarity measure technique is useed extensively toremove the redundancies inherent in the area-based matching method, and also results robust matching at the boundary region. Resulting maches are further improved using iterative support algorithm and post processing. We have obtained good results on randomdot stereogram and real images obtained in our carmera system.

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Development and Application of Image Analysis Program for Investigation of Pore Characteristics in Transverse Surface of Hardwoods

  • Kwon, Oh-Kyung;Lee, Phil-Woo
    • Journal of the Korean Wood Science and Technology
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    • v.26 no.2
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    • pp.29-37
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    • 1998
  • An image analysis program with the function of measuring various quantitative characteristics in the transverse surface of wood was developed using Delphi 2.0. Data on pore characteristics (conditions for image processing, proportion of pores in relationship to other elements, tangential diameter, area, tangential and radial diameter, x and y coordinates of pore center, and geometric coefficients) were saved in text file format. In addition, the pore area histogram in the tangential and radial directions was saved as a BMP (bitmap) type file. Analyses indicated that quantitative characteristics such as the relative radial distribution of pores in a growth ring, pore tangential area histogram, and proportion of pore in lumen area appear to be useful in separating four diffuse-porous woods and four ring-porous woods on the species level.

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Design of Hierarchical Classifier for Classifying Defects of Cold Mill Strip using Neural Networks (신경회로망을 이용한 냉연 표면흠 분류를 위한 계층적 분류기의 설계)

  • Kim, Kyoung-Min;Lyou, Kyoung;Jung, Woo-Yong;Park, Gwi-Tae;Park, Joong-Jo
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.4
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    • pp.499-505
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    • 1998
  • In developing an automated surface inspect algorithm, we have designed a hierarchical classifier using neural network. The defects which exist on the surface of cold mill strip have a scattering or singular distribution. We have considered three major problems, that is preprocessing, feature extraction and defect classification. In preprocessing, Top-hit transform, adaptive thresholding, thinning and noise rejection are used Especially, Top-hit transform using local minimax operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, and histogram ratio features are calculated. The histogram ratio feature is taken from the gray-level image. For defect classification, we suggest a hierarchical structure of which nodes are multilayer neural network classifiers. The proposed algorithm reduced error rate by comparing to one-stage structure.

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