• 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.

• 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 the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.239-245
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• 2004

A hue-based noise-tolerant corner detector is proposed for the exact detection of the real corners in spite of the shadows and random noise. Based on the fact that the hue gradient at the border of the opaque objects' shadow is smaller than the intensity gradient in HSI (hue-saturation-intensity) color space, the effects of shadow are eliminated by introducing the hue-weighted combination of vector gradient to the proposed corner detector. Furthermore, the proposed corner detector is robust to random noise by offsetting the contribution to the corner candidate when the polarities of the color gradients of the pixel pairs are out of phase each other. Results of the experiment show that the proposed corner detector can effectively detect the real corners.

• 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.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.787-795
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• 2014

This paper presents an image registration using Triangulation-based Local Transformation (TLT) applied to the remaining matched points after elimination of the matched points with gross error. The corners extracted using geometric mean-based corner detector are matched using Pearson's correlation coefficient and then accepted as initial matched points only when they satisfy the Left-Right Consistency (LRC) check. We finally accept the remaining matched points whose RANdom SAmple Consensus (RANSAC)-based global transformation (RGT) errors are smaller than a predefined outlier threshold. After Delaunay triangulated irregular networks (TINs) are created using the final matched points on reference and sensed images, respectively, affine transformation is applied to every corresponding triangle and then all the inner pixels of the triangles on the sensed image are transformed to the reference image coordinate. The proposed algorithm was tested using KOMPSAT-2 images and the results showed higher image registration accuracy than the RANSAC-based global transformation.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.73-80
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• 2003

In this paper we propose an algorithm which matches the corresponding feature points between the reference image and the search image. We use Harris's corner detector to find the feature points in both image. For each feature point in the reference image, we can extract the candidate matching points as feature points in the starch image which the normalized correlation coefficient goes greater than a threshold. Finally we determine a corresponding feature points among candidate points by using dynamic programming. In experiments we show results that match feature points in synthetic image and real image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.58-61
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• 2011

방송 콘텐츠 제작에는 카메라, VCR, NLE, 인코더 등의 장비가 사용되고 있으며, VCR 헤더 불량, 테이프 노후화/보관불량, NLE 편집 오류, 인코더 장비 불량 등의 다양한 이유로 콘텐츠에 예기치 않은 비디오 및 오디오 오류가 발생할 수 있다. 이러한 문제점을 해결하기 위하여 콘텐츠에 포함된 다양한 비디오 및 오디오 오류를 자동으로 검사할 수 있는 자동 검사 시스템이 요구된다. 본 논문에서는 이러한 다양한 오류를 자동으로 검사할 수 있는 방법 중 특히 비디오 내에 종종 포함되는 블록 오류를 대상으로 하는 고속 오류 검출 방법을 설명한다. 제안한 방법은 비디오 내의 매 프레임의 코너 수를 계산하고, 시간 증가에 따른 코너 수의 변화량을 검사하여 블록 오류가 포함될 것으로 예상되는 후보 프레임을 찾는 1단계 과정과, 후보 프레임을 대상으로 Adaboost 인식 기술을 사용하여 학습한 분류기를 통해 최종 블록 오류가 포함된 프레임을 검출하는 2단계 과정으로 구성된다. 시스템 구현 실험 결과, 비디오 내에 포함된 블록 오류를 프레임 단위로 정확하게 고속 검출 하는 것이 가능함을 확인하였다. SD급의 경우 실시간 대비 2.3배속 가량의 고속 검사가 가능하고 HD의 경우에도 0.8배속 수준의 고속 검사가 가능하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.60-66
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• 2012

In this paper, we propose abandoned object detection algorithm. When abandoned object was occluded other object, the existing methods cannot detect abandoned object because those methods are not able to estimate the location of abandoned object. In order to overcome this problem, the proposed algorithm extracts the corners around abandoned object. The detected corners are linked to center of abandoned object called by supporters. We can then estimate the location of abandoned object by using supporters. Therefore, the proposed algorithm can detect and estimate the location of abandoned object, when abandoned object is occluded by other object. For this reason, the proposed algorithm can be applied to intelligent surveillance system to prevent bomb terror, which disguises as luggage or box.

• Journal of KIISE:Software and Applications
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• v.33 no.4
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• pp.402-410
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• 2006

This paper presents a method for feature based block motion estimation that uses multi -resolution image sequences to obtain the panoramic images in the continuous ultrasound image sequences. In the conventional block motion estimation method, the centers of motion estimation blocks are set at the predetermined and equally spaced locations. This requires the large blocks to include at least one feature, which inevitably requires long estimation time. In this paper, we propose an adaptive method which locates the center of the motion estimation blocks at the feature points. This make it possible to reduce the block size while keeping the motion estimation accuracy The Harris-Stephen corner detector is used to get the feature points. The comer points tend to group together, which cause the error in the global motion estimation. In order to distribute the feature points as evenly as Possible, the image is firstly divided into regular subregions, and a strongest corner point is selected as a feature in each subregion. The ultrasound Images contain speckle patterns and noise. In order to reduce the noise artifact and reduce the computational time, the proposed method use the multi-resolution image sequences. The first algorithm estimates the motion in the smoothed low resolution image, and the estimated motion is prolongated to the next higher resolution image. By this way the size of search region can be reduced in the higher resolution image. Experiments were performed on three types of ultrasound image sequences. These were shown that the proposed method reduces both the computational time (from 77ms to 44ms) and the displaced frame difference (from 66.02 to 58.08).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.42-45
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• 2011

3차원 영상과 더불어 스테레오 영상의 관심이 늘어남에 따라 좌, 우 영상의 매칭을 통해 변이를 추정하는 연구가 활발하게 진행되고 있다. 본 논문에서는 변이 추정을 위해 많이 사용되는 영역 기반(Block-based)의 전체 탐색 알고리즘보다 효율적이고 계산량이 적은 변이 추정을 할 수 있도록 변이 탐색 범위를 제공해주는 방법을 제안한다. 제안되는 알고리즘은 해리스 코너 포인트 검출기를 이용하여 좌, 우 영상 각각의 특징 점을 추출한 후, 특징 점의 정보를 이용하여 스테레오 매칭을 한다. 스테레오 매칭 시 이를 히스토그램화 하여 좌, 우 영상의 변이 추정을 위한 탐색 범위를 제공한다.