• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.41-51
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• 2010

In the research for driver assistance systems, traffic sign information to the driver must be a very important information. Therefore, the detection system of traffic signs located on the road should be able to handel real-time. To detect the traffic signs, color and shape of traffic signs is to use the information after images obtained using the CCD camera. In the road environment, however, using color information to detect traffic sings will cause many problems due to changes of weather and environmental factors. In this paper, to solve it, the candidate traffic sign regions are detected from road images obtained in a variety of the illumination changes using the HSI eign-color model. And then, using the invariant moment-based SVM classifier to detect traffic signs are proposed. Experimental results show that, traffic sign detection rate is 91%, and the processing time per frame is 0.38sec. Proposed method is useful for real-time intelligent traffic guidance systems can be applied.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.3
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• pp.15-22
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• 1982

This paper presents analytic bending moment solution and resonance diagrams for a uniform beam of infinite length subjected to anaxial force and moving transverse load. Solutions are obtained that are time invariant in a coordinate system moving with the load velocity. The supporting foundation includes damping effects. The influences of the axial force, damping coefficient and load velocity on the beam response are studied. The limiting case of no damping and critial damping are also investigated. The profiles of the mement of the beam is shown graphically for several values of the load speed, the axial force and damping parameters.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1531-1534
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• 2002

Shape description and its corresponding matching algorithm is one of the main concerns in MPEG-7. In this paper, a new method is proposed for shape registration of 2D objects for MPEG-7 Shapes are recognized using the Hu statistical moments in frequency domain. The Hu moments are moment-based descriptors of planar shapes, which are invariant under general translation, rotational, scaling, and reflection transformation. The image is transformed into frequency domain using Fourier Transform. Annular and radial wedge distributions fur the power spectra are extracted. Different statistical features (Hu moments) are found f3r the power spectrum of each selected transformed individual feature. The Euclidean distance of the extracted moment descriptors of the features are found with respect to the shapes in the database. The minimum Euclidean distance is the candidate for the matched shape. The simulation results are performed on the test shapes of MPEG-7.

• 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%.

• 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.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.149-156
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• 2003

This paper proposes a face recognition method based on modified Otsu binarization, Hu moment and linear discriminant analysis (LDA). Proposed method is robust to brightness, contrast, scale, rotation, and translation changes. Modified Otsu binarization can make binary images that have the invariant characteristic in brightness and contrast changes. From edge and multi-level binary images obtained by the threshold method, we compute the 17 dimensional Hu moment and then extract feature vector using LDA algorithm. Especially, our face recognition system is robust to scale, rotation, and translation changes because of using Hu moment. Experimental results showed that our method had almost a superior performance compared with the conventional well-known principal component analysis (PCA) and the method combined PCA and LDA in the perspective of brightness, contrast, scale, rotation, and translation changes with Olivetti Research Laboratory (ORL) database and the AR database.

• 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.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.20-26
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• 2021

In this paper, we studied the rotation angle estimation methods required for image alignment in an image recognition environment. In particular, a rotation angle estimation method applicable to a low specification embedded-based environment was proposed and compared with the existing method using complex moment. The proposed method estimates the rotation angle through similarity mathcing of the 1D projection profile along the radial axis after converting an image into polar coordinates. In addition, it is also possible to select a method of using vector sum of the projection profile, which more simplifies the calculation. Through experiments conducted on binary pattern images and gray-scale images, it was shown that the estimation error of the proposed method is not significantly different from that of complex moment-based method and requires less computation and system resources. For future expansion, a study on how to match the rotation center in gray-scale images will be needed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.22-31
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• 2004

This paper deals with the dynamic hand gesture recognition based on computer vision using neural networks. This paper proposes a global search method and a local search method to recognize the hand gesture. The global search recognizes a hand among the hand candidates through the entire image search, and the local search recognizes and tracks only the hand through the block search. Dynamic hand gesture recognition method is based on the skin-color and shape analysis with the invariant moment and direction information. Starting point and ending point of the dynamic hand gesture are obtained from hand shape. Experiments have been conducted for hand extraction, hand recognition and dynamic hand gesture recognition. Experimental results show the validity of the proposed method.