• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.2
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• pp.100-106
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• 2010

The impact of surface quantization on device parameters of a Si metal oxide semiconductor (MOS) capacitor has been analyzed in the present work. Variation of conduction band bending, position of discrete energy states, variation of surface potential, and the variation of inversion carrier concentration at charge centroid have been analyzed for different gate voltages, substrate doping concentrations and oxide thicknesses. Oxide thickness calculated from the experimental C-V data of a MOS capacitor is different from the actual oxide thickness, since such data include the effect of surface quantization. A correction factor has been developed considering the effect of charge centroid in presence of surface quantization at strong inversion and it has been observed that the correction due to surface quantization is crucial for highly doped substrate with thinner gate oxide.

• 전자공학회논문지 IE
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• v.46 no.3
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• pp.19-25
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• 2009

In this paper, I suggested the character recognition methods which are used the centroid method and included the spherical transform from the rectangle coordination for the character recognition system and obtained the results of the above 78.14% average differential ratio for the character features. The character feature extraction system using the spherical transform method is suggested in this paper, and the possibilities of the method which is get the invariant feature for the character transition using the centroid are suggested through the differential ratio results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.9
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• pp.14-22
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• 2015

TIn this paper, a centering method for an unfocused input character using the spherical domain system and the centering character to use the shift invariant feature for the recognition system is proposed. A system for recognition is implemented using the centroid method with coordinate average values, and the results of an above 78.14% average differential ratio for the character features were obtained. It is possible to extract the shift invariant feature using spherical transformation similar to the human eyeball. The proposed method, which is feature extraction using spherical coordinate transform and transformed extracted data, makes it possible to move the character to the center position of the input plane. Both digital and optical technologies are mixed using a spherical coordinate similar to the 3 dimensional human eyeball for the 2 dimensional plane format. In this paper, a centering character feature using the spherical domain is proposed for character recognition, and possibilities for the recognized possible character shape as well as calculating the differential ratio of the centered character using a centroid method are suggested.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.11-20
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• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.617-623
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• 2008

This paper presents a human motion recognition method using both centroid shift and local basis images. The centroid shift based on 1st moment balance technique is applied to get the robust motion images against position or size changes, the extraction of local basis images based on independent component analysis(ICA) is also applied to find a set of statistically independent motion features, which is included in each motions. Especially, ICA of fixed-point(FP) algorithm based on Newton method is used for being quick to extract a local basis images of motions. The proposed method has been applied to the problem for recognizing the 160(1 person * 10 animals * 16 motions) sign language motion images of 240*215 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than the method using local eigen images and the method using local basis images without centroid shift respectively.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1907_1908
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• 2009

본 논문은 위성사진 데이터에서 경계선 추출에 대한 새로운 알고리즘을 제안한다. 새로운 알고리즘은 조각 선소들을 연결하기 위하여 몇 가지의 Heuristics를 사용하고, CNN(Centroid Neural Network)을 이용해 선소들을 군집화 하는 방법을 제시한다. 제안된 새로운 알고리즘은 실제의 위성영상 데이터에 대한 실험을 통해 그 유용성이 확인 되었다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.564-567
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• 2004

In this thesis, a method is proposed to extract the car plate at the rear side of vehicle using blobs. We first extract the blobs in the input images using intensity variations and calculate the minimum horde. rectangle (MBR) of each blobs. It is followed that we select groups of blobs having similar width, centroid. And then, we try to detect the border lines of car plate and verify whether the area is a car plate or not using NN.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.715-720
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• 2005

This paper presents a hybrid recognition method of first moment of face image and principal component analysis(PCA). First moment is applied to reduce the dimension by shifting to the centroid of image, which is to exclude the needless backgrounds in the face recognitions. PCA is implemented by single layer neural network which has a teaming rule of Foldiak algorithm. It has been used as an alternative method for numerical PCA. PCA is to derive an orthonormal basis which directly leads to dimensionality reduction and possibly to feature extraction of face image. The proposed method has been applied to the problems for recognizing the 48 face images(12 Persons $\ast$ 4 scenes) of 64$\ast$64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.469-478
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• 2010

This paper proposes the effective shape descriptor for 3D foot pose estimation. To reduce processing time, silhouette-based foot image database is built and meta information which involves the 3D pose of the foot is appended to the database. And we proposed a modified Centroid Contour Distance whose size of the feature space is small and performance of pose estimation is better than the others. In order to analyze performance of the descriptor, we evaluate time and spatial complexity with retrieval accuracy, and then compare with the previous methods. Experimental results show that the proposed descriptor is more effective than the previous methods on feature extraction time and pose estimation accuracy.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.575-578
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• 2005

Topographical images, in case of aerial or satellite images, are usually similar in colors and textures, and complex in shapes. Thus we have to use shape features of images for efficiently retrieving a query image from topographical image databases. In this paper, we propose a shape feature extraction method which is suitable for topographical images. This method, which improves the existing projection in the Cartesian coordinates, performs the projection operation in the polar coordinates. This method extracts three attributes, namely the number of region pixels, the boundary pixel length of the region from the centroid, the number of alternations between region and background, along each angular direction of the polar coordinates. It extracts the features of complex shape objects which may have holes and disconnected regions. An advantage of our method is that it is invariant to rotation/scale/translation of images. Finally we show the advantages of our method through experiments by comparing it with CSS which is one of the most successful methods in the area of shape feature extraction