• Journal of Oral Medicine and Pain
• /
• v.30 no.4
• /
• pp.427-432
• /
• 2005

This study have been compared and analyzed voice parameter under the condition of normal voice and auditory condition(noise and music) for 29 patients of orofacial pain and 31 normal people to investigate voice feature and vocal variation for auditory condition of orofacial pain patient. 1. Compared to normal voice, orofacial pain patient showed lower and unstable voice feature which has low F0 rate and high jitter and shimmer rate. 2. Voice of orofacial pain patient showed more relaxed and stable voice feature with low F0 and shimmer rate in the music condition than noise condition. 3. Normal people's voice has no significant difference between music and noise condition even though it has high F0 rate under the noise condition. As a result, orofacial pain patient showed difference of feature and different response for external auditory condition compared to normal voice. Providing of positive emotional environment such as music could be considered for better outcome of oral facial pain patient's functional disability.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.1
• /
• pp.38-43
• /
• 2001

This Paper suggests a new feature for shot detection, using the proposed robust feature from the DC image constructed by DCT DC coefficients in the MPEG video stream, and proposes the characterizing value that reflects the characteristic of kind of video (movie, drama, news, music video etc.). The key frames are pulled out from many frames by using the local minima and maxima of differential of the value. After original frame(not do image) are reconstructed for key frame, indexing process is performed through computing parameters. Key frames that are similar to user's query image are retrieved through computing parameters. It is proved that the proposed methods are better than conventional method from experiments. The retrieval accuracy rate is so high in experiments.

• Journal of the HCI Society of Korea
• /
• v.2 no.2
• /
• pp.35-43
• /
• 2007

This paper presents a system for image matching and recognition based on image feature detection and description techniques from artificial satellite photographs. We propose some kind of parameters from the varied environmental elements happen by image handling process. The essential point of this experiment is analyzes that affects match rate and recognition accuracy when to change of state of each parameter. The proposed system is basically inspired by Lowe's SIFT(Scale-Invariant Transform Feature) algorithm. The descriptors extracted from local affine invariant regions are saved into database, which are defined by k-means performed on the 128-dimensional descriptor vectors on an artificial satellite photographs from Google earth. And then, a label is attached to each cluster of the feature database and acts as guidance for an appeared building's information in the scene from camera. This experiment shows the various parameters and compares the affected results by changing parameters for the process of image matching and recognition. Finally, the implementation and the experimental results for several requests are shown.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.383-388
• /
• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.6
• /
• pp.369-377
• /
• 2023

In the industrial manufacturing sector, quality control is pivotal for minimizing defect rates; inadequate management can result in additional costs and production delays. This study underscores the significance of detecting texture defects in manufactured goods and proposes a more precise defect detection technique. While the DFR(Deep Feature Reconstruction) model adopted an approach based on feature map amalgamation and reconstruction, it had inherent limitations. Consequently, we incorporated a new loss function using statistical methodologies, integrated a skip connection structure, and conducted parameter tuning to overcome constraints. When this enhanced model was applied to the texture category of the MVTec-AD dataset, it recorded a 2.3% higher Defect Segmentation AUC compared to previous methods, and the overall defect detection performance was improved. These findings attest to the significant contribution of the proposed method in defect detection through the reconstruction of feature map combinations.

• Journal of Korea Multimedia Society
• /
• v.9 no.11
• /
• pp.1465-1473
• /
• 2006

In this paper, we present an approach for facial expression recognition using Active Shape Models(ASM) and a state-based model in image sequences. Given an image frame, we use ASM to obtain the shape parameter vector of the model while we locate facial feature points. Then, we can obtain the shape parameter vector set for all the frames of an image sequence. This vector set is converted into a state vector which is one of the three states by the state-based model. In the classification step, we use the k-NN with the proposed similarity measure that is motivated on the observation that the variation-regions of an expression sequence are different from those of other expression sequences. In the experiment with the public database KCFD, we demonstrate that the proposed measure slightly outperforms the binary measure in which the recognition performance of the k-NN with the proposed measure and the existing binary measure show 89.1% and 86.2% respectively when k is 1.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.10a
• /
• pp.265-269
• /
• 2008

Home health care with compact wearable units sounds to be a convenient solution for the elderly people living independently. This paper presents a method to detect fall from the other activities of daily living and also to classify those activities. This kind of ambulatory monitoring enables them to get an emergency help in the case of the fatal fall event and can provide their general health status by observing the activities being performed in daily life. A tri-axial accelerometer sensor is used to get the acceleration anomalies associated with the user's movements. The three axis acceleration data are transferred to the base station sensor node via an IEEE 802.15.4 compliant zigbee module. The base station sensor node sends the data to base station PC for an offline processing. This work shows the feature set preparation using the principal component analysis (PCA) for the designing of neural network. The work includes the most common activities of daily living (ADL) like Rest, Walk and Run along with the detection of fall events from ADL. The angle from the vertical is found to be the most significant feature parameter for classification of fall while mean, standard deviation and FFT coefficients were used as the feature parameter for classifying the other activities under consideration. The accuracy for detection of fall events is 86%. The overall accuracy for ADL and fall is 94%.

• Journal of the Korean Society of Radiology
• /
• v.10 no.8
• /
• pp.645-652
• /
• 2016

In this study, based on the analysis of texture feature values of statistical properties. And we examined the normal and the applicability of the computer-aided diagnosis of cerebral infarction in the brain computed tomography images. The experiment was analyzed to evaluate the ROC curve recognition rate of disease using six parameters representing the feature values of the texture. As a result, it showed average mean 88%, variance 92%, relative smoothness 94%, uniformity of 88%, a high disease recognition rate of entropy 84%. However, it showed a slightly lower disease recognition rate and 58% for skewness. In the analysis using ROC curve, the area under the curve for each parameter indicates 0.886 (p = 0.0001) or more, resulted in a meaningful recognition of the disease. Further, to determine the cut-off values for each parameter are determined to be the prediction of disease through the computer-aided diagnosis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.469-472
• /
• 2005

This paper propose about effective speech feature parameter that have robust character in effect of noise in realizing speech recognition system. Established MFCC that is the basic parameter used to ASR(Automatic Speech Recognition) and DCTCs that use DCT in basic parameter. Also, proposed delta-Cepstrum and delta-delta-Cepstrum parameter that reconstruct Cepstrum to have information for variation of speech. And compared recognition performance in using HMM. For dimension reduction of each parameter LDA algorithm apply and compared recognition. Results are presented reduced dimension delta-delta-Cepstrum parameter in using LDA recognition performance that improve more than existent parameter in noise environment of various condition.

• Korean Journal of Cleft Lip And Palate
• /
• v.5 no.2
• /
• pp.95-108
• /
• 2002

언어 발달의 조기 단계를 이해하기 위한 일환으로 crying은 언어전 발달의 기초 단계로서 여러 학문적 분야에서 많은 연구가 있어왔다. 그러나 구순구개열(CLP))환아의 경우는cry-producing/control mechnism에 variation이 많은 이유로 이 분야의 연구는 거의 없는 실정이다. 이에 본 연구에서는 다음과 같은 의문점을 가지고 CLP환아의 cry feature에 대한분석을 하였다. 첫째, 정상아와 CLP환아의 cry에 전형적인 차이가 있는가? 둘째, CLP환아의 술전, 술후 cry feature에 변화가 있는가? 셋째, cry분석이 CLP환아의 이후 speech disorder에 대한 언어전 평가로서의 가치가 있는가? 넷째, 특정 parameter가 언어전 평가에 적절한 도구로 작용할 수 있는가? 생후 15개월 이내의 CLP 환아 3명과 유사한 나이대의 정상아 8명의 cry에 대한 공기역학 및 음향음성학적 분석을 통해 CLP 환아와 정상아, CLP환아의 술전, 술후 cry특성을 비교 분석하였다. 결과는 다음과 같다. 1 공기역학적 분석 1) airflow는 CLP 환아의 경우 정상아보다 약간 높았고 술 후 약간 증가하였다. 2)폐활량을 나타내는volume에서는 정상아보다 술전 CLP환자의 경우 보상적으로 더 큰 수치를 보였고 술후 약간 증가하였다. 3)강도를 나타내는 parameter(SPL)에서는 정상아 보다 술전 CLP환자의 계측치가 약간 작았으나 술 후 증가하는 양상을 보였다. 2. 음향음성학적 분석 1)기저 주파수 분석시 정상아에 비해 술 전 CLP환자의 경우 계측치가 약간 낮았으나 술 후 증가하여 정상군의 계측치에 근접하였다. 2)강도를 나타내는energy 측정시 정상아에 비해 술 전 CLP계측치가 보상성으로 약간 큰수치를 나타내었고 술 후 약간 더 증가하였다. 3) Shimmer에서는CUI환자의 술후계측치가술전에 비해 현저히 감소하여 정상군의 수치에 근접하였다.