• Title/Summary/Keyword: Moment invariants

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Target Detection Based on Moment Invariants

  • Wang, Jiwu;Sugisaka, Masanori
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.677-680
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    • 2003
  • Perceptual landmarks are an effective solution for a mobile robot realizing steady and reliable long distance navigation. But the prerequisite is those landmarks must be detected and recognized robustly at a higher speed under various lighting conditions. This made image processing more complicated so that its speed and reliability can not be both satisfied at the same time. Color based target detection technique can separate target color regions from non-target color regions in an image with a faster speed, and better results were obtained only under good lighting conditions. Moreover, in the case that there are other things with a target color, we have to consider other target features to tell apart the target from them. Such thing always happens when we detect a target with its single character. On the other hand, we can generally search for only one target for each time so that we can not make use of landmarks efficiently, especially when we want to make more landmarks work together. In this paper, by making use of the moment invariants of each landmark, we can not only search specified target from separated color region but also find multi-target at the same time if necessary. This made the finite landmarks carry on more functions. Because moment invariants were easily used with some low level image processing techniques, such as color based target detection and gradient runs based target detection etc, and moment invariants are more reliable features of each target, the ratio of target detection were improved. Some necessary experiments were carried on to verify its robustness and efficiency of this method.

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Pattern Recognition with Rotation Invariant Multiresolution Features

  • Rodtook, S.;Makhanov, S.S.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1057-1060
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    • 2004
  • We propose new rotation moment invariants based on multiresolution filter bank techniques. The multiresolution pyramid motivates our simple but efficient feature selection procedure based on the fuzzy C-mean clustering, combined with the Mahalanobis distance. The procedure verifies an impact of random noise as well as an interesting and less known impact of noise due to spatial transformations. The recognition accuracy of the proposed techniques has been tested with the preceding moment invariants as well as with some wavelet based schemes. The numerical experiments, with more than 30,000 images, demonstrate a tangible accuracy increase of about 3% for low noise, 8% for the average noise and 15% for high level noise.

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3D Model Retrieval Based on Orthogonal Projections

  • Wei, Liu;Yuanjun, He
    • International Journal of CAD/CAM
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    • v.6 no.1
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    • pp.117-123
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    • 2006
  • Recently with the development of 3D modeling and digitizing tools, more and more models have been created, which leads to the necessity of the technique of 3D mode retrieval system. In this paper we investigate a new method for 3D model retrieval based on orthogonal projections. We assume that 3D models are composed of trigonal meshes. Algorithms process first by a normalization step in which the 3D models are transformed into the canonical coordinates. Then each model is orthogonally projected onto six surfaces of the projected cube which contains it. A following step is feature extraction of the projected images which is done by Moment Invariants and Polar Radius Fourier Transform. The feature vector of each 3D model is composed of the features extracted from projected images with different weights. Our System validates that this means can distinguish 3D models effectively. Experiments show that our method performs quit well.

An Implementation of Image Inspection System for Invariants Moment (불변 모멘트 영상 검사 시스템 구현)

  • Lee, Yong-Joong;Kim, Hak-Bum;Yun, Jin-Su;Kim, Hyoung-Jo;Lee, Yang-Bum
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2449-2451
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    • 2001
  • The purpose of this paper is to develop image inspection system endows an automatic operating and measuring that the moment values are invariant with respect to variable object size and rotation. In this paper, using these moment feature vector with Hu's 7 invariant moment is also given. The characteristics of section which is applied in the mechanics used moment descriptor of invariant moment detection algorithm for image inspection system. Corresponding rates between 94% and 96% have archived for all object tested.

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A Representation and Matching Method for Shape-based Leaf Image Retrieval (모양기반 식물 잎 이미지 검색을 위한 표현 및 매칭 기법)

  • Nam, Yun-Young;Hwang, Een-Jun
    • Journal of KIISE:Software and Applications
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    • v.32 no.11
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    • pp.1013-1020
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    • 2005
  • This paper presents an effective and robust leaf image retrieval system based on shape feature. Specifically, we propose an improved MPP algorithm for more effective representation of leaf images and show a new dynamic matching algorithm that basically revises the Nearest Neighbor search to reduce the matching time. In particular, both leaf shape and leaf arrangement can be sketched in the query for better accuracy and efficiency. In the experiment, we compare our proposed method with other methods including Centroid Contour Distance(CCD), Fourier Descriptor, Curvature Scale Space Descriptor(CSSD), Moment Invariants, and MPP. Experimental results on one thousand leaf images show that our approach achieves a better performance than other methods.

A Study on Feature Information Parsing of Video Image Using Improved Moment Invariant (향상된 불변모멘트를 이용한 동영상 이미지의 특징정보 분석에 관한 연구)

  • Lee, Chang-Soo;Jun, Moon-Seog
    • Journal of Korea Multimedia Society
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    • v.8 no.4
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    • pp.450-460
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    • 2005
  • Today, multimedia information is used on the internet and various social areas by rapid development of computer and communication technology. Therefor, the usage is growing dramatically. Multimedia information analysis system is basically based on text. So, there are many difficult problems like expressing ambiguity of multimedia information, excessive burden of works in appending notes and a lack of objectivity. In this study, we suggest a method which uses color and shape information of multimedia image partitions efficiently analyze a large amount of multimedia information. Partitions use field growth and union method. To extract color information, we use distinctive information which matches with a representative color from converting process from RGB(Red Green Blue) to HSI(Hue Saturation Intensity). Also, we use IMI(Improved Moment Invariants) which target to only outline pixels of an object and execute computing as shape information.

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The 2-Phase Image Retrieval Technique using The Color and Shape Information (색상과 모양 정보를 이용한 2단계 영상 검색 기법)

  • 김봉기;오해석
    • Journal of Korea Multimedia Society
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    • v.1 no.2
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    • pp.173-182
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    • 1998
  • As a result of remarkable developments in multimedia technology, the image database system that can efficiently retrieve image data becomes a core technology of information-oriented society. In this paper, we proposed the 2-phase Image Retrieval System considering both color and shape information as the method of image features extraction for content-based image data retrieval. At the first level, to get color information, with improving and extending the indexing method using color distribution characteristic suggested by Striker et al., i.e. the indexing method considering local color distribution characteristics, the system roughly classifies images through the improved method. At the second level, the system finally retrieves the most similar image from the image queried by the user using the shape information about the image groups classified at the first level. To extract the shape information, we use the Improved Moment Invariants (IMI) that manipulates only the pixels on the edges of objects in order to overcome two main problems of the existing Moment Invariant methods large amount of processing and rotation sensitiveness which can frequently be seen in the Directive Histogram Intersection technique suggested by Jain et al. Experiments have been conducted on 300 automobile images. And we could obtain the more improved results through the comparative test with other methods.

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A Implementation of the Feature-based Hierarchical Image Retrieval System (특징기반 계층적 영상 검색 시스템의 구현)

  • 김봉기;김홍준;김창근
    • Journal of the Korea Society of Computer and Information
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    • v.5 no.2
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    • pp.60-70
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    • 2000
  • As a result of remarkable developments in computer technology, the image retrieval system that can efficiently retrieve image data becomes a core technology of information-oriented society. In this paper, we implemented the Hierarchical Image Retrieval System for content-based image data retrieval. At the first level, to get color information, with improving the indexing method using color distribution characteristic suggested by Striker et al., i.e. the indexing method considering local color distribution characteristics, the system roughly classifies images through the improved method. At the second level, the system finally retrieves the most similar image from the image queried by the user using the shape information about the image groups classified at the first level. To extract the shape information, we use the Improved Moment Invariants(IMI) that manipulates only the pixels on the edges of objects in order to overcome two main problems of the existing Moment Invariant methods large amount of processing and rotation sensitiveness which can frequently be seen in the Directive Histogram Intersection technique suggested by Jain et al. Experiments have been conducted on 300 automobile images And we could obtain the more improved results through the comparative test with other methods.

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INTELLIGENT CONTROL STRATEGY FOR A MOBILE VEHICLE WITH NEURCOMPUTER

  • Sugisaka, Masanori;Wang, Xin;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.815-818
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    • 1997
  • In this paper, an intelligent control strategy for a mobile vehicle, based on the technology of the artificial neural network in a Neurocomputer, is presented. The mobile vehicle learned recognizing and driving knowledge by a neurocomputer. Moment Invariants computation was used to extract the shape of objects. The technologies of both neurocomputer and Neumann-type computer are applied into the control system, and make the mobile vehicle be capable of tracking designated objects and avoiding obstacles.

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Skeleton Tree for Shape-Based Image Retrieval (모양 기반 영상검색을 위한 골격 나무 구조)

  • Park, Jong-Seung
    • The KIPS Transactions:PartB
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    • v.14B no.4
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    • pp.263-272
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    • 2007
  • This paper proposes a skeleton-based hierarchical shape description scheme, called a skeleton tree, for accurate shape-based image retrieval. A skeleton tree represents an object shape as a hierarchical tree where high-level nodes describe parts of coarse trunk regions and low-level nodes describe fine details of boundary regions. Each node refines the shape of its parent node. Most of the noise disturbances are limited to bottom level nodes and the boundary noise is reduced by decreasing weights on the bottom levels. The similarity of two skeleton trees is computed by considering the best match of a skeleton tree to a sub-tree of another skeleton tree. The proposed method uses a hybrid similarity measure by employing both Fourier descriptors and moment invariants in computing the similarity of two skeleton trees. Several experimental results are presented demonstrating the validity of the skeleton tree scheme for the shape description and indexing.