• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1095-1100
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• 2008

In a process of insect foot recognition, footprint segments as basic areas for recognition need to be extracted from scanned insect footprints and appropriate features should be found from the footprint segments in order to discriminate kinds of insects, because the characteristics of the features are important to classify insects. In this paper, we propose methods for automatic footprint segmentation and feature extraction. We use a Trace transform method in order to find out appropriate features from the extracted segments by the above methods. The Trace transform method builds a new type of data structure from the segmented images by functions using parallel trace lines and the new type of data structure has characteristics invariant to translation, rotation and reflection of images. This data structure is converted to Triple features by Diametric and Circus functions, and the Triple features are used for discriminating patterns of insect footprints. In this paper, we show that the Triple features found by the proposed methods are enough distinguishable and appropriate for classifying kinds of insects.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.186-186
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• 2010

개별 블레이드 피치 제어(individual blade pitch control)는 각각의 로터 블레이드의 피치각을 독립적으로 조정함으로써 블레이드에 작용하는 공력을 변화시키는 원리로 풍력 터빈 구조물에 발생하는 동적 피로하중을 저감시키기 위한 제어기법이다. 그러나 개별 피치 제어에 의해 발생하는 각 블레이드의 독립적인 피치 운동은 풍력 터빈 회전자에 비대칭성을 야기하고 구조물의 동적 불안정 현상을 발생시킬 수 있기 때문에 이에 대한 정확한 동적 해석이 선행되어야 한다. 하지만 블레이드의 피치 운동이 반영된 풍력 터빈은 시변계로 간주되어 기존의 시불변계 해석기법을 직접 적용할 수 없기 때문에 동적 해석에 어려움이 있다. 이 논문에서는 각각의 블레이드 피치운동을 주기함수로 근사화 함으로써 풍력 터빈을 주기 시변계로 모형화한다. 그리고 효율적으로 주기 시변계의 근사해를 구하기 위한 변조 좌표 변환(modulated coordinate transformation)기법을 적용하여 블레이드의 피치운동이 반영된 풍력 터빈의 동적 안정성 해석을 수행하였다. 그리고 현재 풍력 터빈의 동적 해석에 활용되는 대표적인 해석 기법인 다중 블레이드 좌표변환(multi-blade coordinate transformation)기법을 이용한 해석보다 정확한 결과를 얻을 수 있음을 보였다.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.3
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• pp.23-31
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• 2002

In this paper we propose a new feature vector for recognition of the facial expression based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are invariant under translation rotation, and scale of an facial expression imege. The Algorithm for recognition of a facial expression contains two parts： the extraction of feature vector and the recognition process. The extraction of feature vector are comprised of modified 2-D conditional moments based on estimated Gibbs distribution for an facial image. In the facial expression recognition phase, we use discrete left-right HMM which is widely used in pattern recognition. In order to evaluate the performance of the proposed scheme, experiments for recognition of four universal expression (anger, fear, happiness, surprise) was conducted with facial image sequences on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 95%.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.883-898
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• 1996

In this paper, we propose improved method to recognize the shape for enhancing the quality of the pattern recognition system by compressing the source images. In the proposed method, we reduced the data amount by skeletonizing the source images using mathematical morphology, and then matched patterns after accomplishing the translation and scale normalization, and rotation invariance on the transformed images. Through the scale normalization, it was possible for the shape recognition at minimum amount of the pixel by giving the weight to the skeleton pixel. As the source images was replaced by the skeleton images, it was possible to reduce the amount of data and computational loads dramatically, and so become much faster even with a smaller memory capacity. Through the experiment, we investigated the optimum scale factor and good result was proved when realizing the pattern recognition system.

• 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.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.132-144
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• 1997

The rotation-invariant pattern recognition filter using circular harmonic function of the wavelet transforme dsreference image by morlet, mexican-hat, and haar wavelt function is proposed. The rotated reference images, the images sililar to the reference image, and the images which are added by random noise are used for the inpt images, and in case of the input images with random noise, they are applied to the recognition after removing the random noise by the transformed moving average method with proper thresholding value and window size. The proposed optical wavelet circular harmonic matched filter (WCHMF) is a type of the matche dfilter, so that it can be applied to the 4f vander lugt optical correlation system. SNR and discrimination capability of the proposed filter are compared with those of the conventional HF, the POCHF, and the BPOCHF. The proper wavelet function for the reference image used in this paper is achieved by applying morlet, mexican-hat, and harr wavelet function ot the proposed filter, and the proposed filter has good SNR and discrimination capability with rotation-invariance in case of the morlet wavelet function.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.267-274
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• 2005

In this paper, we proposed an algorithm which cognize hand pose in real time using only image. Hand recognizes using edge orientation histogram which comes under a constant quantity of 2D appearance because hand pose is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantify, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Besides, principal component space creation time is reduced remarkably because edge directional data is used.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.74-83
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• 1997

We have proposed a composite feature measure which combines the color and shape features of an image for image retrieval. We improved the performance of retrieval based on the efficient color quantization using the Lloyd-Max quanizer and on the Histogram matrix matching method which considers the spatial correlation of quantized color group. We also supplemented the color information using shape information with the Improved Moment Invarlants. We have tested our technique on Image database consisting of 200 actual trademark images. Our experimental results showed that our approach improved the performance compared to the previous method under the various situations such as rotation images, translation images, noise added images, gamma corrected images and so on. The efficiency of retrieval is found to be very high and experimental results are

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.168-173
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• 2012

This paper presents a new human identification algorithm using partial features of the uncovered portion of face when a person wears a mask. After the face area is detected, the feature is extracted from the eye area above the mask. The identification process is performed by comparing the acquired one with the registered features. For extracting features SIFT(scale invariant feature transform) algorithm is used. The extracted features are independent of brightness and size- and rotation-invariant for the image. The experiment results show the effectiveness of the suggested algorithm.

• Journal of the Microelectronics and Packaging Society
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• v.8 no.3
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• pp.1-9
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• 2001

This paper proposes an inspection algorithm for micro ball grid array ($\mu$BGA) solder balls. This algorithm is motivated by the difficulty of finding defect balls by human visual inspection due to their small dimensions. Specifically, it is developed herein an automated vision-based inspection algorithm for $\mu$BGA's, which can inspect solder balls not only for so-called two dimensional errors, such as missings, positions and sizes, but also for height errors. The inspection algorithm uses two dimensional images of $\mu$BGA obtained through special blue illumination, and processes them with a rotation-invariant sub algorithm. It can also detect height errors when a two-camera system is available. Simulation results show that the proposed algorithm is more efficient in detecting ball defects compared with the conventional algorithms.