• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.55-62
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• 2014

This paper proposes a fault detection method utilizing converted images of acoustic emission signals and texture analysis for identifying bearing's multi-faults which frequently occur in an induction motor. The proposed method analyzes three texture features from the converted images of multi-faults: multi-faults image's entropy, homogeneity, and energy. These extracted features are then used as inputs of a fuzzy-ARTMAP to identify each multi-fault including outer-inner, inner-roller, and outer-roller. The experimental results using ten times trials indicate that the proposed method achieves 100% accuracy in the fault classification.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.71-77
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• 2017

Virtual advertisement is an advertising technique that using computer graphic in a media production such as a sports image for inserting product image, logo, advertising slogan, etc. Recently, the image insertion of virtual advertisement is actively spreading due to the satisfaction of technical element for the image insertion of virtual advertisement in sports advertisement by increasing of the image processing technology and the computing performance. In addition, image processing technology for automatic insertion has become an important research field in the virtual advertisement field. In this paper, we propose the method of extracting less-informative region by using image processing technique and machine learning to insert a virtual advertisement automatically in sports image. The proposed method analyzes the brightness level of image through the histogram and extracts the less-informative region using the machine learning method.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.3
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• pp.61-67
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• 2001

In this paper, a method that apply LP algorithm to image for speech recognition is suggested, using both speech and image information for recogniton of korean numeral speech. The input speech signal is pre-emphasized with parameter value 0.95, analyzed for B th LP coefficients using Hamming window, autocorrelation and Levinson-Durbin algorithm. Also, a gray image signal is analyzed for 2-dimensional LP coefficients using autocorrelation and Levinson-Durbin algorithm like speech. These parameters are used for input parameters of neural network using back-propagation algorithm. The recognition experiment was carried out at each noise level, three numeral speechs, '3','5', and '9' were enhanced. Thus, in case of recognizing speech with 2-dimensional LP parameters, it results in a high recognition rate, a low parameter size, and a simple algorithm with no additional feature extraction algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.157-163
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• 2013

In this paper, we propose a human detection technique using thermal imaging camera. The proposed method is useful at night or rainy weather where a visible light imaging cameras is not able to detect human activities. Under the observation that a human is usually brighter than the background in the thermal images, we estimate the preliminary human regions using the statistical confidence measures in the gray-level, brightness histogram. Afterwards, we applied Gaussian filtering and blob labeling techniques to remove the unwanted noise, and gather the scattered of the pixel distributions and the center of gravities of the blobs. In the final step, we exploit the aspect ratio and the area on the unified object region as well as a number of the principal components extracted from the object region images to determine if the detected object is a human. The experimental results show that the proposed method is effective in environments where visible light cameras are not applicable.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.104-113
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• 2000

In this study, we propose facial image recognition based on wavelet transform and neural network. This algorithm is proposed by following processes. First, two gray level images is captured in constant illumination and, after removing input image noise using a gaussian filter, differential image is obtained between background and face input image, and this image has a process of erosion and dilation. Second, a mask is made from dilation image and background and facial image is divided by projecting the mask into face input image Then, characteristic area of square shape that consists of eyes, a nose, a mouth, eyebrows and cheeks is detected by searching the edge of divided face image. Finally, after characteristic vectors are extracted from performing discrete wavelet transform(DWT) of this characteristic area and is normalized, normalized vectors become neural network input vectors. And recognition processing is performed based on neural network learning. Simulation results show recognition rate of 100 % about learned image and 92% about unlearned image.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.15-24
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• 2008

This paper proposes a scheme of global image contrast enhancement using local contrast improvement. Methods of global image contrast enhancement redistribute the image gray level distribution using histogram equalization without considering image properties, and cause the result image to include image pixels with excessive brightness. On the other hand, methods of the block-based local image contrast enhancement have blocking artifacts and a problem of eliminating important image features during an image process to reduce them. In order to solve these problems, the proposed method executes the block-based histogram equalization on temporary images that an input image is divided into various fixed-size blocks. And then it performs the global contrast enhancement by applying the global histogram equalization functions to the original input image. Since the proposed method selects the best histogram equalization function from temporary images that are improved by the block-based local image contrast enhancement, it has the advantages of both the local and global image contrast enhancement approaches.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.41-48
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• 2015

Recently, the spread of 3D printers has been increasing the demand for 3D models. However, the creation of 3D models should have a trained specialist using specialized softwares. This paper is about an algorithm to produce a 3D model from a single sheet of two-dimensional front face photograph, so that ordinary people can easily create 3D models. The background and the foreground are separated from a photo and predetermined constant number vertices are placed on the seperated foreground 2D image at a same interval. The arranged vertex location are extended in three dimensions by using the gray level of the pixel on the vertex and the characteristics of eyebrows and nose of the nomal human face. The separating method of the foreground and the background uses the edge information of the silhouette. The AdaBoost algorithm using the Haar-like feature is also employed to find the location of the eyes and nose. The 3D models obtained by using this algorithm are good enough to use for 3D printing even though some manual treatment might be required a little bit. The algorithm will be useful for providing 3D contents in conjunction with the spread of 3D printers.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.40 no.2
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• pp.37-42
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• 2008

Defects of corrugated board were limiting factors to the corrugated industry's growth. On-line detecting systems of defects are beneficial to increase profits of the corrugated board companies by reducing base paper consumption, increasing process reliability, and increasing productivity. By replacing naked eye inspection of defects to a defects detecting system, continuous inspection without fatigue may guarantee final products quality. The system was developed, which was consisted of line scan CCD camera, lens, illuminating parts, high speed image processor, software, various input parts, and output parts. First installation location of the system was at before fluting process after base paper unwinding, and surface of liner board was inspected by the system. Second installation location was after fluting process and combining process for liner board. Production loss includes ragged appearance of edge, irregular flute shape, wrong combination of flute, score cracking, defects in base paper, and flute cracking. The production loss was analyzed before and after the system installation at a commercial domestic mill. The production loss ratio was defined as a production loss weight per total production weight. The production loss ratio before the installation was decreased a lot from 1.28%(during 3 months before installation) to 0.76%(during 12 months after the first installation) and to 0.25%(during 6 months after the second installation).

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.37 no.5
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• pp.365-374
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• 2011

Introduction: Research on dental bone graft material has been actively conducted. Recently, demineralized dentin matrix material has been developed and introduced. This study examined the effect of demineralized dentin matrix material on bone healing. Subjects and Methods: The patients who received no treatment after extraction were used as the control group and patients who underwent demineralized dentin matrix material application in the extraction socket after extraction were used as the experimental group. Panorama radiography was performed at the baseline and at 3.5 months after graft material placement and CT was taken at 3.5 months after graft material placement for a radiologic evaluation. Bony tissue specimens were collected from the alveolar crest in the middle of the extraction socket using a 2 mm trephine bur after 3.5 months for the histology and hostomorphometric study. Results: 1. On the panoramic view, a higher bone density was observed in the subject group. 2. On the panoramic view, the bone density increased significantly in the extraction socket, from the baseline to 3.5 months: a 7 and 10 gray-level scale was observed in the control and experimental group, respectively (P<0.05). 3. The CT view evaluation at 3.5 months revealed significantly higher bone density in the subject group than the control group (P<0.05). 4. The histological findings showed more active new bone and lamellar bone formation in the subject group. Dentin with osteoinduction ability and enamel with osteoconduction ability appeared. 5. On histomorphometric analysis, the subject group showed significantly more new bone, lamellar bone area and lower soft tissue area (P<0.05). The difference between the groups was significant (P<0.05). Conclusion: Bone healing was improved after the application of demineralized dentin matrix material and there was active new bone and lamellar bone formation.