• Title/Summary/Keyword: Moment invariant feature

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A Study on the Automatic Inspection System using Invariant Moments Algorithm with the Change of Size and Rotation

  • Lee, Yong-Jung;Lee, Yang-Beom;Jeong, Gi-Hwa
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2004.05a
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    • pp.479-485
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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.

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Content-based Rotation Invariant Retrieval of Trademarks (내용기반 회전불변 상표검색)

  • Park, Jin-Geun;Jo, Sang-Hyeon;Choe, Heung-Mun
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.39 no.1
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    • pp.60-66
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    • 2002
  • In this paper, an efficient content-based rotation-invariant retrieval of the trademarks is proposed using the edge-direction histogram for a principal symmetry axis and the moment invariants. Rotation invariant retrieval of trademarks is difficult for the conventional retrieval systems because their feature vectors are not rotation-invariant. In this paper, to obtain rotation invariant feature vectors, in addition to invariant moments, the edge-direction histogram for a principal symmetry axis is introduced and is used to solve the bin shift problem of the histogram resulted from the rotated trademark. Performance evaluation has been carried out for a database of 300 kinds of trademarks including 20 kinds of typical trademarks which are reported to be difficult to retrieve when rotated, and the proposed scheme is proved to retrieve trademarks more efficiently, especially for the rotated trademarks, than the conventional methods.

Conditional Moment-based Classification of Patterns Using Spatial Information Based on Gibbs Random Fields (깁스확률장의 공간정보를 갖는 조건부 모멘트에 의한 패턴분류)

  • Kim, Ju-Sung;Yoon, Myoung-Young
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.6
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    • pp.1636-1645
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    • 1996
  • In this paper we proposed a new scheme for conditional two dimensional (2-D)moment-based classification of patterns on the basis of Gibbs random fields which are will suited for representing spatial continuity that is the characteristic of the most images. This implementation contains two parts: feature extraction and pattern classification. First of all, we extract feature vector which consists of conditional 2-D moments on the basis of estimated Gibbs parameter. Note that the extracted feature vectors are invariant under translation, rotation, size of patterns the corresponding template pattern. In order to evaluate the performance of the proposed scheme, classification experiments with training document sets of characters have been carried out on 486 66Mhz PC. Experiments reveal that the proposed scheme has high classification rate over 94%.

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Underwater Object Recognition Independent of Translation using Ultrasonic Sensor Fabricated with 3-3 type Piezoelectric Composites (3-3형 복합압전체 초음파센서의 수중 물체 변위에 무관한 물체인식 특성)

  • Cho, Hyun-Chul;Lee, Kee-Seong
    • Proceedings of the KIEE Conference
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    • 2001.07c
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    • pp.1484-1486
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    • 2001
  • In this study, The underwater object recognition using ultrasonic sensor fabricated with porous PZT-Polymer 3-3 type composites and invariant moment vector and SOFM(Self Organizing Feature Map) neural networks are presented. The recognition rates for the training data and the testing data were 98% and 94%, respectively.

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A Study on the Automatic Inspection System using Invariant Moments Algorithm with the Change of Size and Rotation

  • 이용중
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.10a
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    • pp.164-169
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    • 2003
  • The purpose of this study is to develop a practical image inspect ion 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 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 inspect ion 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 automat ion when the image inspect ion system developed from this research is applied to the product ive field.

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A Feature-Based Retrieval Technique for Image Database (특징기반 영상 데이터베이스 검색 기법)

  • Kim, Bong-Gi;Oh, Hae-Seok
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.11
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    • pp.2776-2785
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    • 1998
  • An image retrieval system based on image content is a key issue for building and managing large multimedia database, such as art galleries and museums, trademarks and copyrights, and picture archiving and communication system. Therefore, the interest on the subject of content-based image retrieval has been greatly increased for the last few years. This paper proposes a feature-based image retrieval technique which uses a compound feature vector representing both of color and shape of an image. Color information for the feature vector is obtained using the algebraic moment of each pixel of an image based on the property of regional color distribution. Shape information for the feature vector is obtained using the Improved Moment Invariant(IMI) which reduces the quantity of computation and increases retrieval efficiency. In the preprocessing phase for extracting shape feature, we transform a color image into a gray image. Since we make use of the modified DCT algorithm, it is implemented easily and can extract contour in real time. As an experiment, we have compared our method with previous methods using a database consisting of 150 automobile images, and the results of the experiment have shown that our method has the better performance on retrieval effectiveness.

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Content-based Image Retrieval using Color Ratio and Moment of Object Region (객체영역의 컬러비와 모멘트를 이용한 내용기반 영상검색)

  • Kim, Eun-Kyong;Oh, Jun-Taek;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
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    • v.9B no.4
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    • pp.501-508
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    • 2002
  • In this paper, we propose a content-based image retrieval using the color ratio and moment of object region. We acquire an optimal spatial information by the region splitting that utilizes horizontal-vertical projection and dominant color. It is based on hypothesis that an object locates in the center of image. We use color ratio and moment as feature informations. Those are extracted from the splitted regions and have the invariant property for various transformation, and besides, similarity measure utilizes a modified histogram intersection to acquire correlation information between bins in a color histogram. In experimental results, the proposed method shows more flexible and efficient performance than existing methods based on region splitting.

A Study on Implementation of the Object Classification and Inspection System Using Machine Vision (머신비젼을 이용한 물체 분류 및 검사시스템 구현)

  • 전춘기;이원호이탁우영환
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.951-954
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    • 1998
  • This paper describes the implementation of the machine vision system and the method of classifying the objects. Its system described in this paper is consisted of robot, conveyer system, warehouse, and machine vision. This system first recognizes the object on conveyer, and then robot moves it to the warehouse. The position of the object on conveyer is always not constant, because it is not easy to extract the feature of its object and classify it into one of several categories. In this paper, to classify or inspect the pattern of the object, we propose the method of template matching using feature vector such as position invariant moment and mophological operation such as opening and closing. And we indentified an unregistered object using unsuperviser learning method and assigned it to the new pattern. We implemented its system and obtained satisfied results.

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Real-time Sign Object Detection in Subway station using Rotation-invariant Zernike Moment (회전 불변 제르니케 모멘트를 이용한 실시간 지하철 기호 객체 검출)

  • Weon, Sun-Hee;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of Digital Contents Society
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    • v.12 no.3
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    • pp.279-289
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    • 2011
  • The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

2-D Conditional Moment for Recognition of Deformed Letters

  • Yoon, Myoong-Young
    • Journal of Korea Society of Industrial Information Systems
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    • v.6 no.2
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    • pp.16-22
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    • 2001
  • In this paper we mose a new scheme for recognition of deformed letters by extracting feature vectors based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are comprised of 2-D conditional moments which are invariant under translation, rotation, and scale of an image. The Algorithm for pattern recognition of deformed letters contains two parts: the extraction of feature vector and the recognition process. (i) We extract feature vector which consists of an improved 2-D conditional moments on the basis of estimated conditional Gibbs distribution for an image. (ii) In the recognition phase, the minimization of the discrimination cost function for a deformed letters determines the corresponding template pattern. In order to evaluate the performance of the proposed scheme, recognition experiments with a generated document was conducted. on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 96%.

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