• Title/Summary/Keyword: Rotated object

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DCT-Based Images Retrieval for Rotated Images (회전에 견고한 DCT 기반 영상 검색)

  • Kim, Nam-Yee;Song, Ju-Whan;You, Kang-Soo
    • The Journal of the Korea Contents Association
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    • v.11 no.4
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    • pp.67-73
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    • 2011
  • The image retrieval generally shows the same or similar images to a query image as a result. In the case of rotated image, however, its performance tends to be debased significantly. We propose a method to ensure a reliable image retrieval of rotated images as follows; First, to obtain feature points of query/DB images by Harris Corner Detector; and then, utilizing the feature points, to find the object's axis and query/DB images into rotation invariant images with Principal Components Analysis algorithm. We have experimented with 6,000 natural images which are 256 pixels in diameter. They are 1,000 Wang's images and their rotated images by $30^{\circ}$, $45^{\circ}$, $90^{\circ}$, $135^{\circ}$ and $180^{\circ}$. The simulation results show that the proposed method retrieves rotated images more effectively than the conventional method.

A Research on Cylindrical Pill Bottle Recognition with YOLOv8 and ORB

  • Dae-Hyun Kim;Hyo Hyun Choi
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.13-20
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    • 2024
  • This paper introduces a method for generating model images that can identify specific cylindrical medicine containers in videos and investigates data collection techniques. Previous research had separated object detection from specific object recognition, making it challenging to apply automated image stitching. A significant issue was that the coordinate-based object detection method included extraneous information from outside the object area during the image stitching process. To overcome these challenges, this study applies the newly released YOLOv8 (You Only Look Once) segmentation technique to vertically rotating pill bottles video and employs the ORB (Oriented FAST and Rotated BRIEF) feature matching algorithm to automate model image generation. The research findings demonstrate that applying segmentation techniques improves recognition accuracy when identifying specific pill bottles. The model images created with the feature matching algorithm could accurately identify the specific pill bottles.

A 3D Vision Inspection Method using One Camera (1대의 카메라를 이용한 3차원 비전 검사 방법)

  • Jung Cheol-Jin;Huh Kyung Moo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.1
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    • pp.19-26
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    • 2004
  • In this paper, we suggest a 3D vision inspection method which use only one camera. If we have the database of pattern and can recognize the object, and also estimate the rotated shape of the parts, we can inspect the parts using only one image. We used the 3D database and the 2D geometrical pattern matching, and the rotation transition theory about the algorithm. As the results, we could have the capability of the recognition and inspection of the rotated object through the estimation of rotation an81e. We applied our suggested algorithm to the inspection of typical IC and capacitor, and compared our suggested algorithm with the conventional 2D inspection method and the feature space trajectory method.

Model-based 3-D object recognition using hopfield neural network (Hopfield 신경회로망을 이용한 모델 기반형 3차원 물체 인식)

  • 정우상;송호근;김태은;최종수
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.5
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    • pp.60-72
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    • 1996
  • In this paper, a enw model-base three-dimensional (3-D) object recognition mehtod using hopfield network is proposed. To minimize deformation of feature values on 3-D rotation, we select 3-D shape features and 3-D relational features which have rotational invariant characteristics. Then these feature values are normalized to have scale invariant characteristics, also. The input features are matched with model features by optimization process of hopjfield network in the form of two dimensional arrayed neurons. Experimental results on object classification and object matching with the 3-D rotated, scale changed, an dpartial oculued objects show good performance of proposed method.

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Haptic Interaction with Objects Displayed in a Picture based on Surface Normal Estimation (사진 속 피사체의 법선 벡터 예측에 기반한 햅틱 상호 작용)

  • Kim, Seung-Chan;Kwon, Dong-Soo
    • The Journal of Korea Robotics Society
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    • v.8 no.3
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    • pp.179-185
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    • 2013
  • In this paper we propose a haptic interaction system that physically represents the underlying geometry of objects displayed in a 2D picture, i.e., a digital image. To obtain the object's geometry displayed in the picture, we estimate the physical transformation between the object plane and the image plane based on homographic information. We then calculate the rotated surface normal vector of the object's face and place it on the corresponding part in the 2D image. The purpose of this setup is to create a force that can be rendered along with the image without distorting the visual information. We evaluated the proposed haptic rendering system using a set of pictures of objects with different orientations. The experimental results show that the participants reliably identified the geometric configuration by touching the object in the picture. We conclude this paper with a set of applications.

Comparative Analysis of CNN Techniques designed for Rotated Object Classifiation (회전된 객체 분류를 위한 CNN 기법들의 성능 비교 분석)

  • Hee-Il Hahn
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.1
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    • pp.181-187
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    • 2024
  • There are two kinds of well-known CNN methods, the group equivariant CNN and the CNN using steerable filters, which have excellent classification performances for randomly rotated objects in image space. This paper describes their mathematical structures and introduces implementation methods. We implement them, including the existing CNN, which have the same number of filters, then compare and analyze their performances by simulating them with the randomly rotated MNIST. According to the experimental results, the steerable CNN, which shows a classification improvement over the others, has a relatively small number of parameters to learn, so performance degradation is relatively small even when the size of the training dataset is reduced.

Contour-Based Partial Object Recognition Of Elliptical Objects Using Symmetry (대칭특성을 이용한 타원형 객체의 외형기반 부분인식에 관한 연구)

  • Cho June-Suh
    • The KIPS Transactions:PartB
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    • v.13B no.2 s.105
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    • pp.115-120
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    • 2006
  • In This Paper, We Propose The Method To Reconstruct And Estimate Partially Occluded Elliptical Objects In Images From Overlapping And Cutting. We Present The Robust Method For Recognizing Partially Occluded Objects Based On Symmetry Properties, Which Is Based On The Contours Of Elliptical Objects. A Proposed Method Provides Simple Techniques To Reconstruct Occluded Regions Via A Region Copy Using The Symmetry Axis Within An Object. Based On The Estimated Parameters For Partially Occluded Objects, We Perform Object Recognition On The Classifier. Since A Proposed Method Relies On Reconstruction Of The Object Based On The Symmetry Properties Rather Than Statistical Estimates, It Has Proven To Be Remarkably Robust In Recognizing Partially Occluded Objects In The Presence Of Scale Changes, Object Pose, And Rotated Objects With Occlusion, Even Though h Proposed Method Has Minor Limitations Of Object Poses.

Correction of Rotated Frames in Video Sequences Using Modified Mojette Transform (변형된 모젯 변환을 이용한 동영상에서의 회전 프레임 보정)

  • Kim, Ji-Hong
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.42-49
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    • 2013
  • The camera motion is accompanied with the translation and/or the rotation of objects in frames of a video sequence. An unnecessary rotation of objects declines the quality of the moving pictures and in addition is a primary cause of the viewers' fatigue. In this paper, a novel method for correcting rotated frames in video sequences is presented, where the modified Mojette transform is applied to the motion-compensated area in each frame. The Mojette transform is one of discrete Radon transforms, and is modified for correcting the rotated frames as follows. First, the bin values in the Mojette transform are determined by using pixels on the projection line and the interpolation of pixels adjacent to the line. Second, the bin values are calculated only at some area determined by the motion estimation between current and reference frames. Finally, only one bin at each projection is computed for reducing the amount of the calculation in the Mojette transform. Through the simulation carried out on various test video sequences, it is shown that the proposed scheme has good performance for correcting the rotation of frames in moving pictures.

A Study on the Automatic Inspection System using Invariant Moments Algorithm with the Change of Size and Rotation (크기와 회전 변화에 불변 모멘트 알고리즘을 이용한 자동 검사 시스템에 관한 연구)

  • Lee, Yong-Joong
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.3
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    • pp.37-43
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    • 2004
  • The purpose of this study is to develop a practical image inspection system that could recognize it correctly, endowing flexibility to the productive field, although the same object for work will be changed in the size and rotated. In this experiment, it selected a fighter, rotating the direction from $30^{\circ}$ to $45^{\circ}$ simultaneously while changing the size from 1/4 to 1/16, as an object inspection without using another hardware for exclusive image processing. The invariant moments, Hu has suggested, was used as feature vector moment descriptor. As a result of the experiment, the image inspection system developed from this research was operated in real-time regardless of the chance of size and rotation for the object inspection, and it maintained the correspondent rates steadily above from 94% to 96%. Accordingly, it is considered as the flexibility can be considerably endowed to the factory automation when the image inspection system developed from this research is applied to the productive field.