• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.166-169
• /
• 2017

Currently, studies using Deep Learning are actively carried out showing good results in many fields. A template matching method is mainly used to recognize parts mounted on PCB(Printed Circuit Board). However, template matching should have multiple templates depending on the shape, orientation and brightness. And it takes long time to perform matching because it searches for the entire image. And there is also a disadvantage that the recognition rate is considerably low. In this paper, we use the Faster-RCNN method for recognizing PCB components as machine learning for classifying several objects in one image. This method performs better than the template matching method, execution time and recognition.

• Progress in Superconductivity and Cryogenics
• /
• v.11 no.4
• /
• pp.20-24
• /
• 2009

YBCO coated conductors (CC) on the $CeO_2$-buffered IBAD-MgO template were fabricated by metal-organic deposition (MOD) Process with Ba-trifluoroacetate and fluorine-free Y and Cu precursor materials. The precursor solution was coated on $CeO_2$-buffered IBAD MgO templates using the multiple dip-coating method, decomposed into inorganic precursors by pyrolysis up to $400^{\circ}C$ within 3 h, and finally fired at $740{\sim}800^{\circ}C$ in a reduced oxygen atmosphere. Microstructure, texture, and superconducting properties of YBCO films were found highly sensitive to both the firing temperature and time. The high critical current density ($J_C$) of $1.15\;MA/cm^2$ at 77.3K in the self-field could be obtained from $1\;{\mu}m$ thick YBCO CC, fired at $740^{\circ}C$ for 3.5 h, implying that high performance YBCO CC is producible on IBAD MgO template. Further enhancement of $J_C$ values is expected by improving the in-plane texture of $CeO_2$-buffer layer and avoiding the metal substrate contamination.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.4
• /
• pp.451-455
• /
• 2008

In this paper, the k-nearest templates method is proposed to combine multiple classifiers effectively. First, the method decomposes training samples of each class into several subclasses based on the outputs of classifiers to represent a class as multiple models, and estimates a localized template by averaging the outputs for each subclass. The distances between a test sample and templates are then calculated. Lastly, the test sample is assigned to the class that is most frequently represented among the k most similar templates. In this paper, C-means clustering algorithm is used as the decomposition method, and k is automatically chosen according to the intra-class compactness and inter-class separation of a given data set. Since the proposed method uses multiple models per class and refers to k models rather than matches with the most similar one, it could obtain stable and high accuracy. In this paper, experiments on UCI and ELENA database showed that the proposed method performed better than conventional fusion methods.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.2
• /
• pp.1-10
• /
• 2002

This paper presents the new template based human face recognition methods to improve the recognition performance against scale and in-plane rotation variations of face images. To enhance the recognition performance, the templates are generated by linear or nonlinear operation on multiple images including different scales and rotations of faces. As the invariant features to allow for scale and rotation variations of face images, we adopt the affine transformation, the log-polar mapping, and the log-polar image based FFT. The proposed recognition methods are evaluated in terms of the recognition rate and the processing time. Experimental results show that the proposed template based methods lead to higher recognition rate than the single image based one. The affine transformation based face recognition method shows marginally higher recognition rate than those of the log-polar mapping based method and the log-polar image based FFT, while, in the aspect of processing time, the log-polar mapping based method is the fastest one.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.30 no.2
• /
• pp.41-46
• /
• 2020

The characteristics of the residual stress on the types of the substrate was investigated with adjusting the V/III ratio during GaN growth via the HVPE method. GaN single crystal layers were grown on a sapphire substrate and a GaN template under the conditions of V/III ratio 5, 10, and 15, respectively. During GaN growth, multiple hexagonal pits in GaN single crystal were differently revealed in accordance with growth condition and substrate type, and their distribution and depth were measured via optical microscopy(OM) and white light interferometry(WLI). As a result, it was confirmed that the distribution area and depth of hexagonal pit tended to increase as the V/III ratio increased. Moreover, it was found that the residual stress in GaN single crystal decreased as the distribution area and depth of the pit increased through measuring micro Raman spectrophotometer. In the case of GaN growth according to substrate type, the GaN on GaN template showed lower residual stress than the GaN grown on sapphire substrate.

• The KIPS Transactions:PartB
• /
• v.16B no.5
• /
• pp.395-402
• /
• 2009

This paper proposes an approach of a novel facial expression recognition to deal with different intensities to improve a performance of a facial expression recognition. Various expressions and intensities of each person make an affect to decrease the performance of the facial expression recognition. The effect of different intensities of facial expression has been seldom focused on. In this paper, a face expression template and an expression-intensity distribution model are introduced to recognize different facial expression intensities. These techniques, facial expression template and expression-intensity distribution model contribute to improve the performance of facial expression recognition by describing how the shift between multiple interest points in the vicinity of facial parts and facial parts varies for different facial expressions and its intensities. The proposed method has the distinct advantage that facial expression recognition with different intensities can be very easily performed with a simple calibration on video sequences as well as still images. Experimental results show a robustness that the method can recognize facial expression with weak intensities.

• The Journal of the Korea Contents Association
• /
• v.18 no.4
• /
• pp.398-405
• /
• 2018

In the HCI, hand gesture recognition is attracting attention as a method for interaction and information exchange between users and devices along with the development of IT devices. In hand gesture recognition through image processing, palm region detection is a key process contributing to improvement of processing speed and recognition rate. In this paper, we propose a new method for image segmentation between the hand and wrist for palm area detection. The anatomical characteristics of the hand are used to calculate the distance between the iliac bones of the thumb and little finger, which have the widest width, by the horizontal projection histogram of the hand image, and then the palm area is detected by drawing a circle having the width as the diameter. In order to verify the superiority of this method, multiple stage template matching is used to compare and evaluate recognition performance against the four conventional methods for 10 hand gestures. Note that the literatures to offer palm area detection performance evaluation are few although there are many studies on hand gesture recognition.

• Journal of Korea Multimedia Society
• /
• v.19 no.2
• /
• pp.418-427
• /
• 2016

A smart parking management requires to track a vehicle in a indoor parking lot and to detect the place where the vehicle is parked. An advanced parking system watches all space of the parking lot with CCTV cameras. We can use these cameras for vehicles tracking and detection. In order to cover a wide area with a camera, a fisheye lens is used. In this case the shape and size of an moving vehicle vary much with distance and angle to the camera. This makes vehicle detection and tracking difficult. In addition to the fisheye lens, the vehicle headlights also makes vehicle detection and tracking difficult. This paper describes a method of realtime vehicle detection and tracking robust to the harsh situation described above. In each image frame, we update the region of a vehicle and estimate the vehicle movement. First we approximate the shape of a car with a quadrangle and estimate the four sides of the car using multiple histograms of oriented gradient. Second we create a template by applying a distance transform to the car region and estimate the motion of the car with a template matching method.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.2 s.34
• /
• pp.1-10
• /
• 2005

In this Paper, we propose a new block matching a1gorithm that extracts motion vectors from consecutive range data. The proposed method defines a matching metric that integrates intensity, hue, and range. Our algorithm begins matching with a small matching template. If the matching degree is not good enough, we slightly expand the size of a matching template and then repeat the matching process until our matching criterion is satisfied or the predetermined maximum size has been reached. As the iteration proceeds, we adaptively adjust weights of the matching metric by considering the importance of each feature. In the experiments, we show that our block matching approach can work as a promising solution by comparing the proposed method with previously known method in terms of performance.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.927-930
• /
• 2000

Visual features of lip area play an important role in the visual speech information. We are concerned about correct lip area as region of interest (ROI). In this paper, we propose a robust and fast method for locating the mouth corners. Also, we define a region of interest at mouth during speech. A method, which we have used, only uses the horizontal and vertical image operators at mouth area. This searching is performed by fitting the ROI-template to image with illumination control. Most of the lip extraction algorithms are dependent on luminosity of image. We just used the binary image where the variable threshold is applied. The variable threshold varies to illumination condition. In order to control those variations, the gray-tone is converted to binary image by threshold, which is obtained through Multiple Linear Regression Analysis (MLRA) about divided 2D special region. Thus we obtained the region of interest at mouth area, which is the robust extraction about illumination. A region of interest is automatically extracted.