• 한국통신학회논문지
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• 제29권8C호
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• pp.1062-1068
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• 2004

본 논문에서는 정확한 코너점 검출을 위하여 새로운 그레이 레벨 코너점 검출 방법을 제안한다. 새로운 코너 검출자는 코너 영역을 윈도우 크기에 따라서 동심원으로 계층을 나누어 각각의 계층에서의 코너의 각도를 구하여 코너점을 검출하도록 하였다. 또한 계층적 구조를 가지고 처리함으로써 기존의 그레이레벨 코너 검출자보다 더 빠른 처리 속도를 얻을 수 있도록 하였다.

• 제어로봇시스템학회논문지
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• 제17권5호
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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.

• 반도체디스플레이기술학회지
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• 제16권3호
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• pp.53-58
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• 2017

Recently, advance in technology have increased the importance of visual inspection in semiconductor inspection areas. In PCB visual inspection, accurate line estimation is critical to the accuracy of the entire process, since it is utilized in preprocessing steps such as calibration and alignment. We propose a line estimation method that is differently weighted for the line candidates using a histogram of gradient information, when the position of the initial approximate corner points is known. Using the obtained line equation of the outline, corner points can be calculated accurately. The proposed method is compared with the existing method in terms of the accuracy of the detected corner points. The proposed method accurately detects corner points even when the existing method fails. For high-resolution frames of 3.5mega-pixels, the proposed method is performed in 89.01ms.

• Journal of Information Processing Systems
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• 제8권3호
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• pp.399-408
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• 2012

Hand gesture recognition is an important area of research in the field of Human Computer Interaction (HCI). The geometric attributes of the hand play an important role in hand shape reconstruction and gesture recognition. That said, fingertips are one of the important attributes for the detection of hand gestures and can provide valuable information from hand images. Many methods are available in scientific literature for fingertips detection with an open hand but very poor results are available for fingertips detection when the hand is closed. This paper presents a new method for the detection of fingertips in a closed hand using the corner detection method and an advanced edge detection algorithm. It is important to note that the skin color segmentation methodology did not work for fingertips detection in a closed hand. Thus the proposed method applied Gabor filter techniques for the detection of edges and then applied the corner detection algorithm for the detection of fingertips through the edges. To check the accuracy of the method, this method was tested on a vast number of images taken with a webcam. The method resulted in a higher accuracy rate of detections from the images. The method was further implemented on video for testing its validity on real time image capturing. These closed hand fingertips detection would help in controlling an electro-mechanical robotic hand via hand gesture in a natural way.

• 전기학회논문지
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• 제56권10호
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• pp.1865-1867
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• 2007

We propse a novel corner detection algorithm for locating 2D Data Matrix barcode in an image. The proposed method accumulates weight for each cross point defined by every combination of edge points in the image, and detects the corner point of the barcode L-pattern by determining the location of the highest accumulated weight. By designing the weight considering the connectivity of two lines around the cross point, we were able to detect the corner of L-pattern even for the cases that the lines of L-patterns are short. In the experiments, the proposed method showed improved performance compared with the conventional Hough transform based method in terms of detectability and computation time.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권6호
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• pp.792-798
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• 2004

본 논문에서는 웨이퍼 영상에서 다이 위치를 인식하기 위한 새로운 코너점 검출 방법을 제안한다. 웨이퍼 다이 위치 인식은 WSCSP(Wafer Scale Chip Scale Packaging)기술에 필수적인 과정으로서 웨이퍼 윗면의 다이 패턴을 얼마나 정확히 인식하느냐에 따라서 후 공정의 정확도가 결정된다. 본 논문에서는 정확한 다이 위치를 인식하기 위하여 계층적 명암 영상 코너 검출 방법을 제안한다. 새로운 코너 검출자는 코너 영역을 마스크 크기에 따라서 동심원으로 나누어 각각의 동심원에서의 코너성과 방향성을 구하여 정확한 코너점을 검출하도록 하였다. 또한 계층적 구조를 가지고 처리하여 기존의 명암 영상코너 검출자 보다 더 빠른 처리 속도를 얻을 수 있도록 하였다.

• Journal of information and communication convergence engineering
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• 제12권4호
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• pp.263-270
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• 2014

Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.

• 한국멀티미디어학회논문지
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• 제14권5호
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• pp.622-631
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• 2011

Corners play an important role in describing object features for pattern recognition and identification. This paper proposed a fast and adaptive corner detector in both coarse and fine scale, followed by the framework of the curvature scale space (CSS). An adaptive curvature threshold and evaluating of angles of corner candidates are added to original CSS to remove round corners and false corners in the detecting process. The efficiency of proposed method is compared to other popular detectors in both accuracy criteria, stability and time consuming. Results illustrate that the proposed method performs extremely surpass in both areas.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.11-14
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• 2003

In block-based lossy video compression, severe quantization causes discontinuities along block boundaries so that annoying blocking artifacts are visible in decoded video imases. These blocking artifacts significantly decrease the subjective image quality. In order to reduce the blocking artifacts in decoded images, many algorithms have been proposed However studies on so called, corner outliers, have been very limited. Corner outliers make image edges look disconnected from those of neighboring blocks at cross block boundary. In order to solve this problem, we propose a corner outlier detection and compensation algorithm as post-processing in spatial domain The experiment results show that the proposed method provides much improved subjective image quality.

• Journal of Electrical Engineering and Technology
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• 제6권4호
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• pp.580-584
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• 2011

Corner positioning templates are proposed in order to detect the accurate positions of corners that are extracted using 4-directional edge labeling. Top-down and bottom-up directional labeling are used to label the edge segments with four kinds of labels according to their directions. The points whose labels have changed are then determined as corners. The exact positions of the missing corners due to the disconnected edges are detected through the corner positioning templates that are determined according to the labels of start-points and end-points after the two-pass edge labeling. Experiment results show that the proposed method can detect the exact positions of the real corners.