• Tribology and Lubricants
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• v.15 no.2
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• pp.206-211
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• 1999

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.245-248
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• 2007

In this paper, we research the content-based analysis and classification according to the composition of the feature parameter data base for the audio data to implement the audio data index and searching system. Audio data is classified to the primitive various auditory types. We described the analysis and feature extraction method for the feature parameters available to the audio data classification. And we compose the feature parameters data base in the index group unit, then compare and analyze the audio data centering the including level around and index criterion into the audio categories. Based on this result, we compose feature vectors of audio data according to the classification categories, and simulate to classify using discrimination function.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1473-1480
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• 2018

The extraction and recognition of human motion characteristics need to combine biometrics to determine and judge human behavior in the movement and distinguish individual identities. The so-called biometric technology, the specific operation is the use of the body's inherent biological characteristics of individual identity authentication, the most noteworthy feature is the invariance and uniqueness. In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition. And we will use the KTH database to train and test the recognition system. Experiments have been very desirable results.

• The Journal of the Korea Contents Association
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• v.4 no.1
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• pp.18-23
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• 2004

In this paper, we propose a new visual feature extraction method for content-based image retrieval(CBIR) based on wavelet transform which has both spatial-frequency characteristic and multi-resolution characteristic. We extract visual features for each frequency band in wavelet transformation and use them to CBIR. The lowest frequency band involves spacial information of original image. We extract L feature vectors using fuzzy homogeneity in the wavelet domain, which consider both the wavelet coefficients and the spacial information of each coefficient. Also, we extract 3 feature vectors wing the energy values of high frequency bands, and store those to image database. As a query, we retrieve the most similar image from image database according to the 10 largest homograms(normalized fuzzy homogeneity vectors) and 3 energy values. Simulation results show that the proposed method has good accuracy in image retrieval using 90 texture images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1596-1603
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• 2007

In this paper, we experimented by three kind of method for feature parameter, training method and recognition algorithm of most suitable for speech recognition system and considered. We decided speech recognition system of most suitable through two kind of experiment after we make speech recognizer. First, we did an experiment about three kind of feature parameter to evaluate recognition performance of it in speech recognizer using existent MFCC and MFCC new feature parameter that change characteristic space using PCA and ICA. Second, we experimented recognition performance or HMM, SVM and RVM by studying data number. By an experiment until now, feature parameter by ICA showed performance improvement of average 1.5% than MFCC by high linear discrimination from characteristic space. RVM showed performance improvement of maximum 3.25% than HMM in an experiment by decrease of studying data. As such result, effective method for speech recognition system to propose in this paper derives feature parameters using ICA and un recognition using RVM.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.457-469
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• 2003

In this paper, we have proposed the efficient algorithm that can segment the video scene change using a various statistical characteristics obtained from by applying the wavelet transformation for each frames. Our method firstly extracts the histogram features from low frequency subband of wavelet-transformed image and then uses these features to detect the abrupt scene change. Second, it extracts the edge information from applying the mesh method to the high frequency subband of transformed image. We quantify the extracted edge information as the values of variance characteristic of each pixel and use these values to detect the gradual scene change. And we have also proposed an algorithm how extract the proper key frame from segmented video scene. Experiment results show that the proposed method is both very efficient algorithm in segmenting video frames and also is to become the appropriate key frame extraction method.

• Journal of the Korea Fashion and Costume Design Association
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• v.8 no.2
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• pp.47-59
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• 2006

The purpose of this study is to grasp the meaning of retro-fashion, to research the formative feature characteristic and aesthetic values. Retro-fashion is one of the expression of spatiotemporal-eclecticism, The formative of modern Retro-fashion are as follows: First, Retro-fashion based on spatiotemporal-eclecticism have been come from 40s, 50s, 60s, 70s, 80s style of time, and the asia, africa, middle east, latin America in region. Second, the design inspiration and technique is used more primitive crafts and decoration like handcrafted material, handmade ornaments as dyeing and embroidery of bohemian, jacqwuard pattern, oriental beads, applique, new hippie touch, patchwork, smocking, primitive button, woods, ethnic motives. Third, modern Retro-fashion is reflection of human feelings as nostalgia from the past, it supplies the sense of fashion creativity and new ideas.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.522-526
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• 1994

There are great needs for checking machine operation status precisely in the iron and steel plants. Rotating machines such as pumps, compressors, and motors are the most important objects in the plant maintenance. In this paper back-propagation neural network is utilized in diagnosing rotating machines. Like the finger print or the voice print of human, the abnormal vibrations due to axis misalignment, shaft bending, rotor unbalance, bolt loosening, and faults in gear and bearing have their own spectra. Like the pattern recognition technique, characteristic. feature vectors are obtained from the power spectra of vibration signals. Then we apply the characteristic feature vectors to a back propagation neural net for the weight training and pattern recognition.

• Speech Sciences
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• v.15 no.3
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• pp.7-15
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• 2008

This paper proposes the method to extract new feature vectors using the difference between the cepstrum for static characteristics and delta cepstrum for dynamic characteristics in speaker recognition (SR). The difference vector (DV) which it proposes from this paper is containing the static and the dynamic characteristics simultaneously at the intermediate characteristic vector which uses the deference between the static and the dynamic characteristics and as the characteristic vector which is new there is a possibility of doing. Compared to the conventional method, the proposed method can achieve new feature vector without increasing of new parameter, but only need the calculation process for the difference between the cepstrum and delta cepstrum. Experimental results show that the proposed method has a good performance more than 2.03%, on average, compared with conventional method in speaker identification (SI).

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2003.11a
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• pp.235-242
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• 2003

This reserch is to compare and analyze of the residence disposition and feature of ground plan on Seomi 2 Dong in An-dong and Hyun-ri in Mun-gyong. The scope of this reserch concentrated on 33-housed which are 12-housed in Seomi 2 Dong and 21-housed in Hyun-ri. The focus of this reserch is mainly to investigate the characteristic of the site, and ground plans on individual houses. As result of it, there are mostly Yeo-Kan houses (six spans sized) on Seomi 2-dong village in An-Dong on the other hand there are a lot of Straight-Houses in Hyun-ri in Mun-gyong. Otherwise in characteristic of residence, There is dissimilarity between Seomi 2-dong which located in mountainous districts has space organization of utilitarian and Hyun-Ri has justification primacy as a farm village.