• Title/Summary/Keyword: Image Edge

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Depth-map Preprocessing Algorithm Using Two Step Boundary Detection for Boundary Noise Removal (경계 잡음 제거를 위한 2단계 경계 탐색 기반의 깊이지도 전처리 알고리즘)

  • Pak, Young-Gil;Kim, Jun-Ho;Lee, Si-Woong
    • The Journal of the Korea Contents Association
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    • v.14 no.12
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    • pp.555-564
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    • 2014
  • The boundary noise in image syntheses using DIBR consists of noisy pixels that are separated from foreground objects into background region. It is generated mainly by edge misalignment between the reference image and depth map or blurred edge in the reference image. Since hole areas are generally filled with neighboring pixels, boundary noise adjacent to the hole is the main cause of quality degradation in synthesized images. To solve this problem, a new boundary noise removal algorithm using a preprocessing of the depth map is proposed in this paper. The most common way to eliminate boundary noise caused by boundary misalignment is to modify depth map so that the boundary of the depth map can be matched to that of the reference image. Most conventional methods, however, show poor performances of boundary detection especially in blurred edge, because they are based on a simple boundary search algorithm which exploits signal gradient. In the proposed method, a two-step hierarchical approach for boundary detection is adopted which enables effective boundary detection between the transition and background regions. Experimental results show that the proposed method outperforms conventional ones subjectively and objectively.

Environment-Adaptive Image Segmentation Using Color Invariants (칼라 불변량을 이용한 환경 적응적인 영상 분할)

  • Jang, Seok-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.10
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    • pp.71-78
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    • 2010
  • Even though various types of image segmentation methods have been extensively introduced, robustly segmenting images to environmental conditions such as illumination changes, shading, highlight, etc, has been known to be a very difficult task. To resolve the problem in some degree, we propose in this paper an environment-adaptive image segmentation approach using color invariants. The suggested method first introduces several color invariants like W, C, U, N, and H, and automatically measures environmental conditions in which images are captured. It then chooses the most adequate color invariant to environmental factors, and effectively extracts edges using the selected invariant. Experimental results show that the proposed method can robustly perform edge-based segmentation rather than existing methods. We expect that our method will be useful in many real applications which require edge-based image segmentation.

Robust Real-time Face Detection Scheme on Various illumination Conditions (다양한 조명 환경에 강인한 실시간 얼굴확인 기법)

  • Kim, Soo-Hyun;Han, Young-Joon;Cha, Hyung-Tai;Hahn, Hern-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.821-829
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    • 2004
  • A face recognition has been used for verifying and authorizing valid users, but its applications have been restricted according to lighting conditions. In order to minimizing the restricted conditions, this paper proposes a new algorithm of detecting the face from the input image obtained under the irregular lighting condition. First, the proposed algorithm extracts an edge difference image from the input image where a skin color and a face contour are disappeared due to the background color or the lighting direction. In the next step, it extracts a face region using the histogram of the edge difference image and the intensity information. Using the intensity information, the face region is divided into the horizontal regions with feasible facial features. The each of horizontal regions is classified as three groups with the facial features(including eye, nose, and mouth) and the facial features are extracted using empirical properties of the facial features. Only when the facial features satisfy their topological rules, the face region is considered as a face. It has been proved by the experiments that the proposed algorithm can detect faces even when the large portion of face contour is lost due to the inadequate lighting condition or the image background color is similar to the skin color.

Fusion Matching According to Land Cover Property of High Resolution Images (고해상도 위성영상의 토지피복 특성에 따른 혼합정합)

  • Lee, Hyoseong;Park, Byunguk;Ahn, Kiweon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.6_1
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    • pp.583-590
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    • 2012
  • This study proposes fusion image matching method according to land cover property to generate a detailed DEM using the high resolution IKONOS-2 stereo pair. A classified image, consists of building, crop-land, forest, road and shadow-water, is produced by color image with four bands. Edges and points are also extracted from panchromatic image. Matching is performed by the cross-correlation computing after five classes are automatically selected in a reference image. In each of building class, crop-land class, forest class and road class, matching was performed by the grid and edge, only grid, only grid, grid and point, respectively. Shadow-water class was excepted in the matching because this area causes excessive error of the DEM. As the results, edge line, building and residential area could be expressed more dense than DEM by the conventional method.

3D Point Clouds Encryption Method and Analysis of Encryption Ratio in Holographic Reconstruction Image (3D 공간정보 암호화 기법과 홀로그래픽 복원영상의 암호화 효율 분석)

  • Choi, Hyun-Jun;Seo, Young-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.9
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    • pp.1703-1710
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    • 2017
  • This paper propose a 3D point clouds (depth) security technique for digital holographic display service. Image contents encryption is a method to provide only authorized right owners with the original image information by encrypting the entire image or a part of the image. The proposed method detected an edge from a depth and performed quad tree decomposition, and then performed encryption. And encrypts the most significant block among the divided blocks. The encryption effect was evaluated numerically and visually. The experimental results showed that encrypting only 0.43% of the entire data was enough to hide the constants of the original depth. By analyzing the encryption amount and the visual characteristics, we verified a relationship between the threshold for detecting an edge-map. As the threshold for detecting an edge increased, the encryption ratio decreased with respect to the encryption amount.

Technique of Seam-Line Extraction for Automatic Image Mosaic Generation (자동 모자이크 영상제작을 위한 접합선 추출기법에 관한 연구)

  • Song, Nak-Hyeon;Lee, Sung-Hun;Oh, Kum-Hui;Cho, Woo-Sug
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.1
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    • pp.47-53
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    • 2007
  • Satellite image mosaicking is essential for image interpretation and analysis especially for a large area such as the Korean Peninsula. This paper proposed the technique of automatic seam-line extraction and the method of creating image mosaic in automated fashion. The seam-line to minimize artificial discontinuity was extracted using Minimum Absolute Gray Difference Sum algorithm with constraint condition on search-area width and Canny Edge Detection algorithm. To maintain the radiometric balance among images acquired at different time epochs, we utilized Match Cumulative Frequency method. Experimental results showed that edge detection algorithm extracted the seam-lines significantly well along linear features such as roads and rivers.

A Study on Implementation of the High Speed Feature Extraction System Based on Block Type Classification (블록 유형 분류 알고리즘 기반 고속 특징추출 시스템 구현에 관한 연구)

  • Lee, Juseong;An, Ho-Myoung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.3
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    • pp.186-191
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    • 2019
  • In this paper, we propose a implementation approach of the high-speed feature extraction algorithm. The proposed method is based on the block type classification algorithm which reduces the computation time when target macro block is divided to smooth block type that has no image features. It is quantitatively identified that occurs at 29.5% of the total image using 200 standard test images with $64{\times}64$ macro block size. This means that within a standard test image containing various image information, 29.5% can reduce the complexity of the operation. When the proposed approach is applied to the Canny edge detection, the required latency of the edge detection can be completely eliminated, such as 2D derivative filter, gradient magnitude/direction computation, non-maximal suppression, adaptive threshold calculation, hysteresis thresholding. Also, it is expected that operation time of the feature detection can be reduced by applying block type classification algorithm to various feature extraction algorithms in this way.

Adult Image Filtering using Support Vector Mchine (Support Vector Machine을 이용한 유해 이미지 분류)

  • Song, Chull-Hwan;Yoo, Seong-Joon
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.10c
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    • pp.218-221
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    • 2006
  • 본 논문은 인터넷의 대표적인 문제점중의 하나인 Adult Image 분류 연구에 대해 기술한다. 특히 우리는 이러한 Adult Image를 분류하기 위한 Data Set을 5가지 타입으로 구성한다. 이러한 각 Image에 대해 Color, Gradient, Edge Direction 특성의 Feature들을 추출하고 이를 Histogram으로 구성한다. 이렇게 구성된 Histogram을 Support Vector Machine에 적용하여 Adult Image를 분류한다. 그 결과, 우리는 8250개의 Test Set에 대하여 Recall(96.53%), Precision(97.33%), False Positive(2.96%), F-Measure(96.93%)의 성능 결과를 보여준다.

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Extraction of Feature Points Using a Line-Edge Detector (선경계 검출에 의한 특징점 추출)

  • Kim, Ji-Hong;Kim, Nam-Chul
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1427-1430
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    • 1987
  • The feature points of an image play a very important role in understanding the image. Especially, when an image is composed of lines, vertices of the image offer informations about its property and structure. In this paper, a series of process for extracting feature points from actual IC image is described. This result can be used to acquire CIF ( Caltech Intermediate Form ) file.

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Range Image Segmentation Based on Polynomial Function Approximation (다항식 함수 근사화에 근거한 거리 영상 분할)

  • 임영수;조택일;박규호
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.9
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    • pp.1448-1455
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    • 1990
  • In this paper, a range image segmentation method is proposed. This method consists of an initial segmentation stage by discontinuous edge detection and surface type labeling based on the sign of the principal curvatures. Initially type labeled image is oversegmented, this image is merged via stepwise optimal region merging stage based on polynomial function approxiamtion. The successful segmentation results are presented for two synthetic range images with noise and a real-world ERIM range image.

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