• 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.

• 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.

• 한국컴퓨터정보학회논문지
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• 제12권1호
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• pp.261-267
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• 2007

최근 교통문제 해결을 위한 하나의 방안으로 첨단교통체계(ITS)에 관한 연구가 활발히 진행 중이다. 또한 도로 상에서 차량을 검출하기 위한 다양한 방법들이 제시되고 있다. 본 논문에서는 영상처리 기술을 이용하여 이동하는 차량을 검출하는 차량검지 시스템을 개발하여 도로 이용자에게 신속한 정보를 제공하고자 한다. 또한 차량을 검출하기 위해 효율적이고 하드웨어로 구현이 쉬운 알고리즘을 개발하는데 목적이 있다. CCD 카메라를 이용하여 도로 영상을 촬영하고, 모폴로지 기법을 적용하여 영상으로부터 특징점을 추출하고, 추출된 특징점 간의 이동벡터를 구하여 움직이는 차량영역을 검출한다. 제안된 알고리즘을 실제 도로 영상에서 실험한 결과 처리시간이 단축되었으며, 차량 검출에서 좋은 결과를 얻을 수 있었다.

• 한국표면공학회지
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• 제55권6호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.3981-4004
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• 2019

This paper proposes a novel method for locating objects in real space from a single remote image and measuring actual distances between them by automatic detection and perspective transformation. The dimensions of the real space are known in advance. First, the corner points of the interested region are detected from an image using deep learning. Then, based on the corner points, the region of interest (ROI) is extracted and made proportional to real space by applying warp-perspective transformation. Finally, the objects are detected and mapped to the real-world location. Removing distortion from the image using camera calibration improves the accuracy in most of the cases. The deep learning framework Darknet is used for detection, and necessary modifications are made to integrate perspective transformation, camera calibration, un-distortion, etc. Experiments are performed with two types of cameras, one with barrel and the other with pincushion distortions. The results show that the difference between calculated distances and measured on real space with measurement tapes are very small; approximately 1 cm on an average. Furthermore, automatic corner detection allows the system to be used with any type of camera that has a fixed pose or in motion; using more points significantly enhances the accuracy of real-world mapping even without camera calibration. Perspective transformation also increases the object detection efficiency by making unified sizes of all objects.

• 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.

• 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.

• 대한원격탐사학회지
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• 제30권6호
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• pp.769-776
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• 2014

동일 대상에 대한 두 영상의 등록을 위해서는 두 영상에 공통적으로 존재하는 특징점을 검출하고 검출된 특징점 간의 대응관계를 찾는 과정이 필수적이다. 본 논문에서는 화소의 밝기 변화를 측정할 수 있는 그레디언트 행렬의 고유치 기하평균에 기반한 새로운 특징점 검출기를 제안한다. 제안하는 특징점 검출기는 그레디언트 행렬의 두 고유치의 기하평균 크기에 비례하고 기하 평균 크기가 동일한 경유 두 고유치의 상대적인 차이에 비례하여 가변적으로 변하는 특성을 가진다. 제안한 특징점 검출기의 성능 평가를 위해 다양한 종류의 코너가 존재하는 합성 영상과 항공 영상을 기준 영상으로 사용하여 코너 검출의 위치 오차를 분석하였다. 제안한 검출기의 위치 오차는 Gaussian smoothing scale 조건하에서 대표적인 코너 검출기인 Harris detector의 위치 오차보다 작은 결과가 얻어졌다.

• 방송공학회논문지
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• 제22권3호
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• pp.313-320
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• 2017

HEVC 표준에 적용된 인루프 필터링 방법인 De-blocking filter와 SAO(Sample Adaptive Offset)은 영상의 블록화 현상(Blocking artifacts)과 ringing artifacts를 효과적으로 제거하여 부호화 효율 및 주관적 화질 향상을 달성하였다. 하지만, 인루프 필터링 사용에도 불구하고, Corner outlier artifacts라 불리는 블록 경계의 모서리 부분에서 발생하는 2차원 형태의 블록화 현상은 쉽게 제거하지 못하는 문제점을 보인다. 본 논문에서는 Corner outlier 픽셀 탐색 및 판단과정, 해당 outlier 픽셀의 필터링 방법을 통하여 이러한 artifacts를 감소시키는 방법을 제안한다. 실험결과, 제안하는 방법은 화면간 예측에서 약간의 압축 효율 향상을 보였으며, 특히 영상의 주관적 화질 측면에서 개선된 효과를 나타내었다.

• International Journal of Contents
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• 제13권1호
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• pp.68-75
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• 2017

Interactive Typography is a process where a user communicates by interacting with text and a moving factor. This research covers interactive typography using real-time response to a user's gesture. In order to form a language-independent system, preprocessing of entered text data presents image data. This preprocessing is followed by recognizing the image data and the setting interaction points. This is done using computer vision technology such as the Harris corner detector and contour detection. User interaction is achieved using skeleton information tracked by a depth camera. By synchronizing the user's skeleton information acquired by Kinect (a depth camera,) and the typography components (interaction points), all user gestures are linked with the typography in real time. An experiment was conducted, in both English and Korean, where users showed an 81% satisfaction level using an interactive typography system where text components showed discrete movements in accordance with the users' gestures. Through this experiment, it was possible to ascertain that sensibility varied depending on the size and the speed of the text and interactive alteration. The results show that interactive typography can potentially be an accurate communication tool, and not merely a uniform text transmission system.