• Title/Summary/Keyword: edge histogram

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Automatic Extraction of Rescue Requests from Drone Images: Focused on Urban Area Images (드론영상에서 구조요청자 자동추출 방안: 도심지역 촬영영상을 중심으로)

  • Park, Changmin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.3
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    • pp.37-44
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    • 2019
  • In this study, we propose the automatic extraction method of Rescue Requests from Drone Images. A central object is extracted from each image by using central object extraction method[7] before classification. A central object in an images are defined as a set of regions that is lined around center of the image and has significant texture distribution against its surrounding. In this case of artificial objects, edge of straight line is often found, and texture is regular and directive. However, natural object's case is not. Such characteristics are extracted using Edge direction histogram energy and texture Gabor energy. The Edge direction histogram energy calculated based on the direction of only non-circular edges. The texture Gabor energy is calculated based on the 24-dimension Gebor filter bank. Maximum and minimum energy along direction in Gabor filter dictionary is selected. Finally, the extracted rescue requestor object areas using the dominant features of the objects. Through experiments, we obtain accuracy of more than 75% for extraction method using each features.

A Survey of Shape Descriptors in Computer Vision (컴퓨터비전에서 사용되는 모양표시자의 현황)

  • 유헌우;장동식
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.2
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    • pp.131-139
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    • 2003
  • Shape descriptors play an important role in systems for object recognition, retrieval, registration, and analysis. Seven well-known descriptors including MPEG-7 visual descriptors arebriefly reviewed and a new robust pattern recognition descriptor is proposed. Performance comparison among descriptors are presented. Experiments show that the newly proposed descriptor yields better performance results than Fourier, invariant moment, and edge histogram descriptors.

A New Automatic Thresholding of Gray-Level Images Based on Maximum Entropy of Two-Dimensional Pixel Histogram (이웃 화소간 이차원 히스토그램 엔트로피 최대화를 이용한 명도영상 임계값 설정)

  • 김호연;남윤석;김혜규;박치항
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.77-80
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    • 2000
  • In this paper, we present a new automatic thresholding algorithm based on maximum entropy of two-dimensional pixel histogram. While most of the previous algorithms select thresholds depending only on the histogram of gray level itself in the image, the presented algorithm considers 2D relational histogram of gray levels of two adjacent pixels in the image. Thus, the new algorithm tends to leave salient edge features on the image after thresholding. The experimental results show the good performance of the presented algorithm.

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Fast Extraction of Edge Histogram in DCT Domain based on MPEG-7 (MPEG-7 기반 DCT영역에서의 에지히스토그램 고속 추출 기법)

  • Eom Min-Young;Choe Yoon-Sik;Won Chee-Sun;Nam Jae-Yeal
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.4 s.310
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    • pp.19-26
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    • 2006
  • In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by the only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

Content Based Image Retrieval Based on A Novel Image Block Technique Combining Color and Edge Features

  • Kwon, Goo-Rak;Haoming, Zou;Park, Sei-Seung
    • Journal of information and communication convergence engineering
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    • v.8 no.2
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    • pp.185-190
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    • 2010
  • In this paper we propose the CBIR algorithm which is based on a novel image block method that combined both color and edge feature. The main drawback of global histogram representation is dependent of the color without spatial or shape information, a new image block method that divided the image to 8 related blocks which contained more information of the image is utilized to extract image feature. Based on these 8 blocks, histogram equalization and edge detection techniques are also used for image retrieval. The experimental results show that the proposed image block method has better ability of characterizing the image contents than traditional block method and can perform the retrieval system efficiently.

Wavelet-Based Edge Detection Using Local Histogram Analysis in Images (영상에서 웨이블렛 기반 로컬 히스토그램 분석을 이용한 에지검출)

  • Park, Min-Joon;Kwon, Min-Jun;Kim, Gi-Hun;Shim, Han-Seul;Kim, Dong-Wook;Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.359-371
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    • 2011
  • Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.

An Efficient Pedestrian Recognition Method based on PCA Reconstruction and HOG Feature Descriptor (PCA 복원과 HOG 특징 기술자 기반의 효율적인 보행자 인식 방법)

  • Kim, Cheol-Mun;Baek, Yeul-Min;Kim, Whoi-Yul
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.10
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    • pp.162-170
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    • 2013
  • In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

Object Recognition by Pyramid Matching of Color Cooccurrence Histogram (컬러 동시발생 히스토그램의 피라미드 매칭에 의한 물체 인식)

  • Bang, H.B.;Lee, S.H.;Suh, I.H.;Park, M.K.;Kim, S.H.;Hong, S.K.
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.304-306
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    • 2007
  • Methods of Object recognition from camera image are to compare features of color. edge or pattern with model in a general way. SIFT(scale-invariant feature transform) has good performance but that has high complexity of computation. Using simple color histogram has low complexity. but low performance. In this paper we represent a model as a color cooccurrence histogram. and we improve performance using pyramid matching. The color cooccurrence histogram keeps track of the number of pairs of certain colored pixels that occur at certain separation distances in image space. The color cooccurrence histogram adds geometric information to the normal color histogram. We suggest object recognition by pyramid matching of color cooccurrence histogram.

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The Implementing a Color, Edge, Optical Flow based on Mixed Algorithm for Shot Boundary Improvement (샷 경계검출 개선을 위한 칼라, 엣지, 옵티컬플로우 기반의 혼합형 알고리즘 구현)

  • Park, Seo Rin;Lim, Yang Mi
    • Journal of Korea Multimedia Society
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    • v.21 no.8
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    • pp.829-836
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    • 2018
  • This study attempts to detect a shot boundary in films(or dramas) based on the length of a sequence. As films or dramas use scene change effects a lot, the issues regarding the effects are more diverse than those used in surveillance cameras, sports videos, medical care and security. Visual techniques used in films are focused on the human sense of aesthetic therefore, it is difficult to solve the errors in shot boundary detection with the method employed in surveillance cameras. In order to define the errors arisen from the scene change effects between the images and resolve those issues, the mixed algorithm based upon color histogram, edge histogram, and optical flow was implemented. The shot boundary data from this study will be used when analysing the configuration of meaningful shots in sequences in the future.

A Study on Improved Edge Detection Method of Aerial Image Using Histogram Computation (Histogram 연산을 이용한 항공 촬영 영상의 향상된 Edge Detection 방법 연구)

  • Shin, Kwang-Seong;Shin, Seong-Yoon;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.137-138
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    • 2018
  • 이미지의 픽셀 기반 처리는 한 픽셀의 값을 변환하고 다른 픽셀의 값에 관계없이 현재 픽셀의 값에 따라 변환하는 프로세스를 의미한다. 픽셀 기반 처리는 이미지 변환, 이미지 향상 및 이미지 합성과 같은 많은 분야에서 가장 기본적인 작업이다. 본 논문에서는 히스토그램 연산과 같은 영상의 전처리 과정이 경계 검출 결과에 미치는 상호 연관성에 대해 알아보고 픽셀 기반의 처리를 이용하여 효과적으로 영상의 윤곽을 찾는 방법을 제안한다.

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