• Journal of KIISE:Databases
• /
• v.36 no.6
• /
• pp.446-454
• /
• 2009

Among various region detector and shape feature extraction method, MSER(Maximally Stable Extremal Region) and SIFT and its variant methods are popularly used in computer vision application. However, since SIFT is sensitive to the illumination change and MSER is sensitive to the scale change, it is not easy to apply the image similarity retrieval. In this paper, we present a Scale and Rotation Invariant Region Feature(SRIRF) descriptor using scale pyramid, MSER and affine normalization. The proposed SRIRF method is robust to scale, rotation, illumination change of image since it uses the affine normalization and the scale pyramid. We have tested the SRIRF method on various images. Experimental results demonstrate that the retrieval performance of the SRIRF method is about 20%, 38%, 11%, 24% better than those of traditional SIFT, PCA-SIFT, CE-SIFT and SURF, respectively.

• The KIPS Transactions:PartB
• /
• v.17B no.3
• /
• pp.227-232
• /
• 2010

This paper proposes the real time lip reading method in the embedded environment. The embedded environment has the limited sources to use compared to existing PC environment, so it is hard to drive the lip reading system with existing PC environment in the embedded environment in real time. To solve the problem, this paper suggests detection methods of lip region, feature extraction of lips, and awareness methods of phonetic words suitable to the embedded environment. First, it detects the face region by using face color information to find out the accurate lip region and then detects the exact lip region by finding the position of both eyes from the detected face region and using the geometric relations. To detect strong features of lighting variables by the changing surroundings, histogram matching, lip folding, and RASTA filter were applied, and the properties extracted by using the principal component analysis(PCA) were used for recognition. The result of the test has shown the processing speed between 1.15 and 2.35 sec. according to vocalizations in the embedded environment of CPU 806Mhz, RAM 128MB specifications and obtained 77% of recognition as 139 among 180 words were recognized.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.11
• /
• pp.2127-2134
• /
• 2007

The electronic learning helped a learner to overcome the time restriction by providing mobility, instantly and flexibility but the restriction in connection with space on cable computer remained unsolved. Accordingly, the electronic learning has tendency to change into mobile learning environment which allows a learner to overcome time and spatial restriction. However, these mobile devices have a limitation to awareness of learning contents provided over the realtime video movie due to its small display size. Therefore, this paper suggests a technique according to the following priority: for a real time learning image, extract region of study for region of interest, rescale the real time image to its proper size suitable for the display device, and then make it displayed on a wireless PDA. As a result of the experiment, we reduced the calculating time by sampling the field centering on learning contents adaptively and computing the field best suited for device size of the user effectively.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.6
• /
• pp.35-43
• /
• 2009

In the Computer Aided Diagnosis(CAD) System, the efficient way of classifying nodules from chest CT images of a patient is to perform the classification of the remaining part after the pulmonary vessel extraction. During the pulmonary vessel extraction, due to the small difference between the vessel and nodule features in imaging studies such as CT scans after having an injection of contrast, nodule maybe extracted along with the pulmonary vessel. Therefore, the pulmonary vessel extraction method plays an important role in the nodule classification process. In this paper, we propose a nodule reclassification method based on vessel thickness analysis. The proposed method consist of four steps, lung region searching step, vessel extraction and thinning step, vessel topology formation and correction step and the reclassification of nodule in the vessel candidate step. The radiologists helped us to compare the accuracy of the CAD system using the proposed method and the accuracy of general one. Experimental results show that the proposed method can extract pulmonary vessels and reclassify false-positive nodules accurately.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.41 no.12
• /
• pp.27-34
• /
• 2004

The study on the RF substrate circuit is necessary to model RF output characteristics of deep submicron MOSFETs below 0.2$\mum$ gate length that have bun commercialized by the recent development of Si submicron process. In this paper, direct extraction methods are developed to apply for a simple substrate resistance model as well as another substrate model with connecting resistance and capacitance in parallel. Using these extraction methods, better agreement with measured Y22-parameter up to 30 GHz is achieved for 0.15$\mum$ CMOS device by using the parallel RC substrate model rather than the simple resistance one, demonstrating the RF accuracy of the parallel model and extraction technique. Using this model, bias and gate length dependent curves of substrate parameters in the RF region are obtained by increasing drain voltage of 0 to 1.2V at deep submicron devices with various gate lengths of 0.11 to 0.5㎛ These new extraction data will greatly contribute to developing a scalable RF nonlinear substrate model.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.6C
• /
• pp.585-592
• /
• 2005

One of the most important things in the researches on diseases is to attach more importance to prevention of a disease and preservation of health than to treatment of a disease, also to foods rather than to medicines. In this context, the most significant concern in examining a patient is to find the presence of disease, and, if any, to diaguose the type of disease, after which a pharmacotherapy is followed. In this paper, various diagnosis methods of Oriental medicines are discussed. And ocular inspection, the most important method among the 4 disease diagnoses of Oriental medicines, is studied. Observing a person's shape and color has been the major method for ocular inspection, which usually has been dependent upon doctor's intuition as of these days. We are developing an automatic system which provides objective basic data for ocular inspection. As the first stage, we applied the signal processing techniques to automatic feature extraction of faces for ocular inspection. Firstly, facial regions are extracted from the point of frontal view, which was followed by extraction of their features. The experiment applied to 20 persons showed that frontal face regions are perfectly extracted, as well as their features, such as eyes, eyebrows, noses and mouths. Future work will seek to address the issues of morphological operation for a few unfinished extraction results, such as combined hair and eyebrows.

• Journal of Environmental Science International
• /
• v.15 no.3
• /
• pp.279-286
• /
• 2006

Electrokinetic technique was considered in removing arsenic from the abandoned mining tails. In order to estimate the removal characteristics of arsenic, the sequential extraction analysis and desorption experiment were carried out prior to the application of electrokientic process. The result of sequential extraction analysis indicated that the water soluble and exchangeable fraction, easily leachable to ground water, were very low as much as about 2.5% and the fraction except residual (38.3%), possibly extractable under very acidic or alkalic environment, was about 59%. In the result of desorption test using four different kinds of electrolytes, the mixture of citric acid and sodium dodecyl sulfate (SDS) showed the highest desorption efficiency as much as 77.3%. The removal efficiencies of arsenic from mining tailings by electrokinetic process under the different electrolyte environments were slightly low and resulted in the following order: citric acid + SDS (18.6%) > 0.1 $NHNO_3$ (8.1%) > HAc (7.4%) > Distilled water(6.6%). Also, arsenic in soil matrix was moved favorably in the direction of anodic rather than cathodic region, which is opposite trend with cationic metal ions generally existing in soil, because anionic form of arsenic is dominated in acidic soil caused by the movement of acid front form anode.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.1
• /
• pp.12-18
• /
• 2013

Motor imagery classification in electroencephalography (EEG)-based brain-computer interface (BCI) systems is an important research area. To simplify the complexity of the classification, selected power bands and electrode channels have been widely used to extract and select features from raw EEG signals, but there is still a loss in classification accuracy in the state-of- the-art approaches. To solve this problem, we propose a discriminative feature extraction algorithm based on power bands with principle component analysis (PCA). First, the raw EEG signals from the motor cortex area were filtered using a bandpass filter with ${\mu}$ and ${\beta}$ bands. This research considered the power bands within a 0.4 second epoch to select the optimal feature space region. Next, the total feature dimensions were reduced by PCA and transformed into a final feature vector set. The selected features were classified by applying a support vector machine (SVM). The proposed method was compared with a state-of-art power band feature and shown to improve classification accuracy.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.12
• /
• pp.3995-4003
• /
• 2000

This paper describes a method that extracts the region of car-licence plates in color images of private and commercial cars. To extract car-licence plates, we use the feature that car-licence plate regions have regular colors according to the kinds of cars. In this paper, we propose the method that combines H component of HSI color model and Q component of YIQ color model. To improve efficiency of the process, we cxplore lines ill a car image by a regular interval in a bottom-up style. As a result, the extraction rates by only H-component. only by Q- component. and by combined Hand Q, are 53.6%, 82.1%, and 94.6% respectively.

• Korean Journal of Cognitive Science
• /
• v.11 no.2
• /
• pp.53-58
• /
• 2000

This paper reconstructs local region of a facial expression image from extracted feature points of facial expression image using FCM(Fuzzy C-Meang) clustering algorithm with Gabor wavelets. The feature extraction in a face is two steps. In the first step, we accomplish the edge extraction of main components of face using average value of 2-D Gabor wavelets coefficient histogram of image and in the next step, extract final feature points from the extracted edge information using FCM clustering algorithm. This study presents that the principal components of facial expression images can be reconstructed with only a few feature points extracted from FCM clustering algorithm. It can also be applied to objects recognition as well as facial expressions recognition.