• 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.

• Proceedings of the Optical Society of Korea Conference
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• 2007.07a
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• pp.339-340
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• 2007

• 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.

• 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.

• 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.

• 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.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.419-428
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• 2011

This paper suggests a judgement method for an inclined plane before entrance of it and the detection of obstacle position. Main idea is started from the assumption that obstacle is always on the bottom plane, and corner appears at this position. The process to detect the obstacle consists of three steps. First the 3D data using stereo matching is acquired to detect an obstacle. Second a bottom plane is extracted by using limit condition. Last the obstacle position is found by using Harris corner detection. Obstacle position detection on an inclined plane was verified by outdoor and indoor experiment. In error analysis, it is confirmed that an average error of obstacle detection in outdoor was larger than the error in indoor but the error are within about 0.030 m. This method will be applied to unmanned vehicles to navigate under various environment.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.1-9
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• 2008

In this paper, we proposed automatic face detection and tracking which is robustness in rotation. To detect a face image in complicated background and various illuminating conditions, we used face skin color detection. we used Harris corner detector for extract facial feature points. After that, we need to track these feature points. In traditional method, Lucas-Kanade feature tracker doesn't delete useless feature points by occlusion in current scene (face rotation or out of camera). So we proposed the estimation function, which delete useless feature points. The method of delete useless feature points is estimation value at each pyramidal level. When the face was occlusion, we deleted these feature points. This can be robustness to face rotation and out of camera. In experimental results, we assess that using estimation function is better than traditional feature tracker.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1053-1059
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• 2010

This paper treats the DIS (Digital Image Stabilization) problem subject to base motions such as translation, rotation and zoom. For the local motion estimation from a raw image, the Harris corner detection algorithm is exploited to extract feature points, and comparing those of consecutive images, the zoom ratio (scale factor) is computed. For the global motion estimation, an equivalent model is derived to account for a 3-dimensional composite motion from which the center point and Euler angle can be determined. Finally, the motion compensation follows. To show the effectiveness of the present DIS scheme, experimental results for synthetic images are illustrated.