• Title/Summary/Keyword: Corner detection

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Comparative Study of Corner and Feature Extractors for Real-Time Object Recognition in Image Processing

  • Mohapatra, Arpita;Sarangi, Sunita;Patnaik, Srikanta;Sabut, Sukant
    • Journal of information and communication convergence engineering
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    • v.12 no.4
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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.

Post-Processing for Reducing Corner Outliers (Corner outlier 제거를 위한 후처리 기법)

  • 홍윤표;전병우
    • Proceedings of the IEEK Conference
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    • 2003.11a
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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.

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Development of Vehicle Detection System by Using Motion Vector of Corner Point (특징점의 모션벡터를 이용한 차량 검지 시스템 개발)

  • Han, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.1 s.45
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    • pp.261-267
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    • 2007
  • The research about Intelligence Transport Systems(ITS) is actively studied for the traffic problem solution recently. Also, the various methods to detect vehicles moving in the roads are studied. This research using image processing technology is to give the drivers the road information quickly by developing Vehicle Detection System that detects through traffics. Purpose or this research is developing efficient algorithm to facilitate hardware composition. We use morphology method to extract corner points in the images captured by CCD camera. Also, the proposed algorithm detects vehicle's moving area by using motion vectors between corner points. The experiments of the proposed algorithm whose processing time was shortened show good results in vehicle detection on the live road images.

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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 the Korean institute of surface 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.

Remote Distance Measurement from a Single Image by Automatic Detection and Perspective Correction

  • Layek, Md Abu;Chung, TaeChoong;Huh, Eui-Nam
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.8
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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.

Detection of Junctions via Accumulation of Connectivity-based Weight in Image Space : Applications for Locating 2D Barcode (영상 공간에서의 연결성 기반 가중치 누적을 통한 코너점 검출: 이차원 바코드 검출에의 응용)

  • Kim, Jeong-Tae;Song, Jin-Young
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.10
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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.

A Fast Adaptive Corner Detection Based on Curvature Scale Space

  • Nguyen, Van Hau;Woo, Kyung-Haeng;Choi, Won-Ho
    • Journal of Korea Multimedia Society
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    • v.14 no.5
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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.

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.

The Filtering Method to Reduce Corner Outlier Artifacts in HEVC (Corner Outlier Artifacts를 감소시키기 위한 HEVC 필터링 방법)

  • Ko, Kyung-hwan
    • Journal of Broadcast Engineering
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    • v.22 no.3
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    • pp.313-320
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    • 2017
  • The In-loop filtering methods such as de-blocking filter and SAO(Sample Adaptive Offset) applied to the HEVC standard achieves coding efficiency and subjective quality improvement by reducing the blocking artifacts and the ringing artifacts. However, despite the use of In-loop filtering methods, the artifacts called a corner outlier occurring at the corner points of block boundaries are not removed. In this paper, the corner outlier artifacts are reduced by the detection, determination, and filtering processes on the corner outlier pixels. Experimental results show that the proposed method improves the subjective picture quality and slightly increases the coding efficiency in Inter prediction.

Interactive Typography System using Combined Corner and Contour Detection

  • Lim, Sooyeon;Kim, Sangwook
    • International Journal of Contents
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    • v.13 no.1
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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.