• Title/Summary/Keyword: Image Edge

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Urban Change Detection Between Heterogeneous Images Using the Edge Information (이종 공간 데이터를 활용한 에지 정보 기반 도시 지역 변화 탐지)

  • Jae Hong, Oh;Chang No, Lee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.259-266
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    • 2015
  • Change detection using the heterogeneous data such as aerial images, aerial LiDAR (Light Detection And Ranging), and satellite images needs to be developed to efficiently monitor the complicating land use change. We approached this problem not relying on the intensity value of the geospatial image, but by using RECC(Relative Edge Cross Correlation) which is based on the edge information over the urban and suburban area. The experiment was carried out for the aerial LiDAR data with high-resolution Kompsat-2 and −3 images. We derived the optimal window size and threshold value for RECC-based change detection, and then we observed the overall change detection accuracy of 80% by comparing the results to the manually acquired reference data.

An Evaluation and Combination of Noise Reduction Filtering and Edge Detection Filtering for the Feature Element Selection in Stereo Matching (스테레오 정합 특징 요소 선택을 위한 잡음 감소 필터링과 에지 검출 필터링의 성능 평가와 결합)

  • Moon, Chang-Gi;Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.23 no.4
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    • pp.273-285
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    • 2007
  • Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

Using Mean Shift Algorithm and Self-adaptive Canny Algorithm for I mprovement of Edge Detection (경계선 검출의 향상을 위한 Mean Shift 알고리즘과 자기 적응적 Canny 알고리즘의 활용)

  • Shin, Seong-Yoon;Pyo, Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.7
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    • pp.33-40
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    • 2009
  • Edge detection is very significant in low level image processing. However, majority edge detection methods are not only effective enough cause of the noise points' influence, even not flexible enough to different input images. In order to sort these problems, in this paper an algorithm is presented that has an extra noise reduction stage at first, and then automatically selects the both thresholds depending on gradient amplitude histogram and intra class minimum variance. Using this algorithm, can fade out almost all of the sensitive noise points, and calculate the propose thresholds for different images without setting up the practical parameters artificially, and then choose edge pixels by fuzzy algorithm. In finally, get the better result than the former Canny algorithm.

Weather Classification and Fog Detection using Hierarchical Image Tree Model and k-mean Segmentation in Single Outdoor Image (싱글 야외 영상에서 계층적 이미지 트리 모델과 k-평균 세분화를 이용한 날씨 분류와 안개 검출)

  • Park, Ki-Hong
    • Journal of Digital Contents Society
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    • v.18 no.8
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    • pp.1635-1640
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    • 2017
  • In this paper, a hierarchical image tree model for weather classification is defined in a single outdoor image, and a weather classification algorithm using image intensity and k-mean segmentation image is proposed. In the first level of the hierarchical image tree model, the indoor and outdoor images are distinguished. Whether the outdoor image is daytime, night, or sunrise/sunset image is judged using the intensity and the k-means segmentation image at the second level. In the last level, if it is classified as daytime image at the second level, it is finally estimated whether it is sunny or foggy image based on edge map and fog rate. Some experiments are conducted so as to verify the weather classification, and as a result, the proposed method shows that weather features are effectively detected in a given image.

A study of age estimation from occluded images (가림이 있는 얼굴 영상의 나이 인식 연구)

  • Choi, Sung Eun
    • Journal of Platform Technology
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    • v.10 no.3
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    • pp.44-50
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    • 2022
  • Research on facial age estimation is being actively conducted because it is used in various application fields. Facial images taken in various environments often have occlusions, and there is a problem in that performance of age estimation is degraded. Therefore, we propose age estimation method by creating an occluded part using image extrapolation technology to improve the age estimation performance of an occluded face image. In order to confirm the effect of occlusion in the image on the age estimation performance, an image with occlusion is generated using a mask image. The occluded part of facial image is restored using SpiralNet, which is one of the image extrapolation techniques, and it is a method to create an occluded part while crossing the edge of an image. Experimental results show that age estimation performance of occluded facial image is significantly degraded. It was confirmed that the age estimation performance is improved when using a face image with reconstructed occlusions using SpiralNet by experiments.

A Study on the Multi-function Processor Unit Implementation for Binary Image Processing (이진영상처리를 위한 다기능 프로세서 장치구현에 관한 연구)

  • 기재조;허윤석;이대영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.7
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    • pp.970-979
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    • 1993
  • In this paper, a multi-function processor unit is implemented for binary image processing. This unit consists of a set of address generatior, window pipeline register, look up table, control unit, and two local memories .The merits of multi-function processor unit are more simpler than basic SAP and improved disposal speed. A simple software selection give the various choices of image sizes and it can process the function of smoothing, thinning, feature extraction, and edge detection, selectively or sequentially.

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A Motion Adaptive Multi-Frame Interpolation Algorithm (움직임 적응형 멀티프레임 보간 알고리즘)

  • 김희철;채종석;최철호;권병헌;최명렬
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.54-57
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    • 2000
  • In this paper, we propose a new interpolation method by using the motion between two moving image frames. In the proposed method, the movement is detected by using neighborhood pixels of target pixel in the past frame and the present frame. Then, H-shaped pseudomedian filter (below HPMED) is used for the still part of the image and Delta-shaped interpolation filter (below $\Delta$-shaped) for used in the moving part of the image. We detect the movement by comparing the differences between pixels in 4${\times}$5 window of the past frame and the present frame; the difference has a critical value. We simultaneously accomplish checking PSNR(peak signal noise ratio) and subjective assessment that is placed the focus on edge characteristic for assessment of result in computer simulation. The results show that the proposed adaptive method is better than the conventional methods.

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Image quality enhancement using signal subspace method (신호 부공간 기법을 이용한 영상화질 향상)

  • Lee, Ki-Seung;Doh, Won;Youn, Dae-Hee
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.11
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    • pp.72-82
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    • 1996
  • In this paper, newly developed algorithm for enhancing images corrupted by white gaussian noise is proposed. In the method proposed here, image is subdivided into a number of subblocks, and each block is separated into cimponents corresponding to signal and noise subspaces, respectively through the signal subspace method. A clean signal is then estimated form the signal subspace by the adaptive wiener filtering. The decomposition of noisy signal into noise and signal subspaces in is implemented by eigendecomposition of covariance matrix for noisy image, and by performing blockwise KLT (karhunen loeve transformation) using eigenvector. To reduce the perceptual noise level and distortion, wiener filtering is implementd by adaptively adjusting noise level according to activity characteristics of given block. Simulation results show the effectiveness of proposed method. In particular, edge bluring effects are reduced compared to the previous methods.

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Development of Frost Thickness Measurement Method Using Optical Technique (광학적 기법에 의한 Frost 두께 측정방법의 개발)

  • Jeong, Jae-Hong;Yoon, Sang-Youl;Kim, Kyung-Chun
    • Proceedings of the KSME Conference
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    • 2001.06d
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    • pp.654-659
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    • 2001
  • A new non-contact method of the frost thickness measurement has been developed. The method is based on the digital image processing technique to identify the reflection edge of the image captured by a CCD camera under laser sheet light illumination. To insure the accuracy of frost layer thickness, an in-situ calibration procedure is carried out with a calibration target with 0.5mm holes. Using the mapping function obtained by the calibration procedure, the contour of frost surface can be estimated with sub-pixel resolutions. The developed method is applied to study the effect of cooling plate temperature on the frost thickness in a small low speed wind tunnel.

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Multi-Valued Image Entropy Coding for input-width reduction of LCD source drivers

  • Sasaki, Hisashi;Arai, Tooru;Hachiuma, Masayuki;Masuko, Akira;Taguchi, Takashi
    • 한국정보디스플레이학회:학술대회논문집
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    • 2004.08a
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    • pp.149-152
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    • 2004
  • A new joint source channel coding reduces both input-width and average current consumption to transmit image data to LCD source drivers. As a source coding, it is based on entropy coding of differential pulse code modulation scheme, especially using median edge detector of image predictor. As a channel coding, it is not a simple pulse amplitude modulation, but linked by source entropy to reduce average amplitude. Simulation results show 1/4 width is achievable by 16-valued transmission with keeping conventional current consumption (0.36 to 1.3).

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