• Title/Summary/Keyword: Harris Corner

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Harris Corner Detection for Eyes Detection in Facial Images

  • Navastara, Dini Adni;Koo, Kyung-Mo;Park, Hyun-Jun;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.373-376
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    • 2013
  • Nowadays, eyes detection is required and considered as the most important step in several applications, such as eye tracking, face identification and recognition, facial expression analysis and iris detection. This paper presents the eyes detection in facial images using Harris corner detection. Firstly, Haar-like features for face detection is used to detect a face region in an image. To separate the region of the eyes from a whole face region, the projection function is applied in this paper. At the last step, Harris corner detection is used to detect the eyes location. In experimental results, the eyes location on both grayscale and color facial images were detected accurately and effectively.

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Applicability of Projective Transformation for Constructing Correspondences among Corners in Building Facade Imagery (건물벽면 영상내 코너점의 대응관계 구성을 위한 사영변환행렬의 적용성)

  • Seo, Suyoung
    • Korean Journal of Remote Sensing
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    • v.30 no.6
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    • pp.709-717
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    • 2014
  • The objective of this study is to analyze the degree of correspondences among corners found in building facade imagery when the projective transformation parameters are applied to. Additionally, an appropriate corner detection operator is determined through experiments. Modeling of the shape of a building has been studied in numerous approaches using various type of data such as aerial imagery, aerial lidar scanner imagery, terrestrial imagery, and terrestrial lidar imagery. This study compared the Harris operator with FAST operator and found that the Harris operator is superior in extracting major corner points. After extracting corners using the Harris operator and assessing the degree of correspondence among corners in difference images, real corresponding corners were found to be located in the closest distance. The experiment of the projective transformation with varying corners shows that more corner control points with a good distribution enhances the accuracy of the correspondences.

A Study on rendering image denoising using Harris corner detection and median filtering (Harris corner 검출법과 median filtering을 이용한 렌더링 이미지 노이즈 제거에 관한 연구)

  • You, Hojoon;Oh, Jaemu;Hwang, Hyeonsang;Lee, Eui Chul
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.960-962
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    • 2021
  • Monte Carlo 렌더링은 모든 빛을 광원에서부터 추적하는 것 대신, 몇 개의 빛의 경로만을 추적해서 이들의 평균으로 화소값을 정해 이미지를 만드는 방법이다. 여기서 추적하는 빛이 많다면 이미지가 사실적으로 만들어질 수 있지만 연산량이 증가한다. 따라서 적은 빛의 경로를 추적하여 렌더링을 수행하여 이미지를 만들고, 노이즈를 제거해서 많은 양의 빛을 추적하여 렌더링을 한 이미지와 유사하게 만들려는 연구가 많이 진행되고 있다. 그러나 이러한 연구들은 많은 연산량을 요구하기 때문에 고성능의 기기 사양을 요구한다. 따라서 본 연구에서는 저사양의 기기에서 활용할 수 있도록 Harris corner 검출법과 median filtering을 활용한 렌더링 이미지 노이즈 제거 연구를 수행했다.

Automated Generation of Corner Detectors Using Genetic Programming (Genetic Programming을 이용한 코너 검출자의 자동생성)

  • Kim, Young-Kyun;Seo, Ki-Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.4
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    • pp.580-585
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    • 2009
  • This paper introduces GP(Genetic Programming) based corner detectors for an image processing. Various empirical algorithms have been studied to improve computational speed and accuracy including typical approaches, such as Harris and SUSAN. The these techniques are highly efficient, because properties of corner points are inspected and reflected into the algorithms. However these approaches are limited in discovering an innovative algorithm. In this study, we try to discover a more efficient technique by creating corner detector automatically using evolution of GP. The proposed method is compared to the existing corner detectors for test images.

Character Detection in Complex Scene Image using Harris Corner Detector (해리스 코너 검출기를 이용한 배경 영상에서의 문자 검출)

  • Kim, Min-ha;Kim, Mi-kyung;Cha, Eui-young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.97-100
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    • 2013
  • In this paper, we propose a detection method of the character rather than cursive, containing many components of the vertical and horizontal direction in complex background image. The characters have many dense corners but the background has few sparse corners. So we use harris corner detector and cluster the corners by using the position of the detected corners for detecting character regions. To merge or filter character regions, we analysis a histogram of gray image of character regions. In each improved region, we compare histograms of R, G, B channels to detect characters.

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DCT-Based Images Retrieval for Rotated Images (회전에 견고한 DCT 기반 영상 검색)

  • Kim, Nam-Yee;Song, Ju-Whan;You, Kang-Soo
    • The Journal of the Korea Contents Association
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    • v.11 no.4
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    • pp.67-73
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    • 2011
  • The image retrieval generally shows the same or similar images to a query image as a result. In the case of rotated image, however, its performance tends to be debased significantly. We propose a method to ensure a reliable image retrieval of rotated images as follows; First, to obtain feature points of query/DB images by Harris Corner Detector; and then, utilizing the feature points, to find the object's axis and query/DB images into rotation invariant images with Principal Components Analysis algorithm. We have experimented with 6,000 natural images which are 256 pixels in diameter. They are 1,000 Wang's images and their rotated images by $30^{\circ}$, $45^{\circ}$, $90^{\circ}$, $135^{\circ}$ and $180^{\circ}$. The simulation results show that the proposed method retrieves rotated images more effectively than the conventional method.

Feature Detection using Geometric Mean of Eigenvalues of Gradient Matrix (그레디언트 행렬 고유치의 기하 평균을 이용한 특징점 검출)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.30 no.6
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    • pp.769-776
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    • 2014
  • It is necessary to detect the feature points existing simultaneously in both images and then find the corresponding relationship between the detected feature points. We propose a new feature detector based on geometric mean of two eigenvalues of gradient matrix which is able to measure the change of pixel intensities. The corner response of the proposed detector is proportional to the geometric mean and also the difference of two eigenvalues in the case of same geometric mean. We analyzed the localization error of the feature detection using aerial image and artificial image with various types of corners. The localization error of the proposed detector was smaller than that of the typical corner detector, Harris detector.

Defect detection of vacuum insulation panel using image analysis based on corner feature detection (코너 특정점 기반의 영상분석을 활용한 진공단열재 결함 검출)

  • Kim, Beom-Soo;Yang, Jeonghyeon;Kim, Yeonwon
    • Journal of Surface Science and Engineering
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    • v.55 no.6
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    • pp.398-402
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    • 2022
  • Vacuum Insulation Panel (VIP) is an high energy efficient insulation system that facilitate slim but high insulation performance, based on based on a porous core material evacuated and encapsulated in a multi-barrier envelope. Although VIP has been on the market for decades now, it wasn't until recently that efforts have been initiated to propose a standard on aging testing. One of the issues regarding VIP is its durability and aging due to pressure and moisture dependent increase of the initial low thermal conductivity with time. It is hard to visually determine at an early stage. Recently, a method of analyzing the damage on the a material surface by applying image processing technology has been widely used. These techniques provide fast and accurate data with a non-destructive way. In this study, the surface VIP images were analyzed using the Harris corner detection algorithm. As a result, 171,333 corner points in the normal packaging were detected, whereas 32,895 of the defective packaging, which were less than the normal packaging. were detected. These results are considered to provide meaningful information for the determination of VIP condition.

Text Region Extraction from Videos using the Harris Corner Detector (해리스 코너 검출기를 이용한 비디오 자막 영역 추출)

  • Kim, Won-Jun;Kim, Chang-Ick
    • Journal of KIISE:Software and Applications
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    • v.34 no.7
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    • pp.646-654
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    • 2007
  • In recent years, the use of text inserted into TV contents has grown to provide viewers with better visual understanding. In this paper, video text is defined as superimposed text region located of the bottom of video. Video text extraction is the first step for video information retrieval and video indexing. Most of video text detection and extraction methods in the previous work are based on text color, contrast between text and background, edge, character filter, and so on. However, the video text extraction has big problems due to low resolution of video and complex background. To solve these problems, we propose a method to extract text from videos using the Harris corner detector. The proposed algorithm consists of four steps: corer map generation using the Harris corner detector, extraction of text candidates considering density of comers, text region determination using labeling, and post-processing. The proposed algorithm is language independent and can be applied to texts with various colors. Text region update between frames is also exploited to reduce the processing time. Experiments are performed on diverse videos to confirm the efficiency of the proposed method.