• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.94-102
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• 2010

In recent years, embedded systems such as cellular phones, Portable Multimedia Player, intelligent appliance, automobile engine control are reshaping the way people live, work, and play. Thereby, services application to guarantee various requirements of users become increasingly sophisticated and complicated, such embedded computing platforms use real-time operating systems (RTOSs) with time determinism. These RTOSs must not only provide predictable services but must also be efficient and small in size. Kernel services should also be deterministic by specifying how long each service call will take to execute. Having this information allows the application designers to better plan their real-time application software so as not to miss the deadline of each task. In this paper, we present the complete generalized real-time scheduling algorithm using multi-dimensional methodology to determine the highest priority in the ready list with 2r levels of priorities in a constant time without additional memory overhead.

• Journal of IKEEE
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• v.24 no.1
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• pp.225-231
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• 2020

In this paper, we propose a method to accelerate BWN based on FPGA with limited resources for embedded system. Because of the limited number of logic elements available, a single computing unit capable of handling Conv-layer, FC-layer of various sizes must be designed and reused. Also, if the input feature map can not be parallel processed at one time, the output must be calculated by reading the inputs several times. Since the number of available BRAM modules is limited, the number of data bits in the BWN accelerator must be minimized. The image classification processing time of the BWN accelerator is superior when compared with a embedded CPU and is faster than a desktop PC and 50% slower than a GPU system. Since the BWN accelerator uses a slow clock of 50MHz, it can be seen that the BWN accelerator is advantageous in performance versus power.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.705-711
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• 2011

This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.304-308
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• 2010

In this paper, we propose a new method of recognizing the vehicle license plate using color space, morphological characteristics and ART2 algorithm. Morphological characteristics of old and/or new style vehicle license plate among the candidate regions are applied to remove noise areas using 8-directional contour tracking algorithm, then follow by the extraction of vehicle plate. From the extracted license plate area, plate morphological characteristics of each region are removed. After that, labeling algorithm to extract the individual characters are then combined. The classified individual character and numeric codes are applied to the ART2 algorithm for the learning and recognition. In order to evaluate the performance of our proposed extraction and recognition of vehicle license method, we have run experiments on 100 green plates and white plates. Experimental results shown that the proposed license plate extraction and recognition method was effective.

• Smart Media Journal
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• v.5 no.1
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• pp.15-23
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• 2016

This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.4
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• pp.1-7
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• 2003

This is basic study for analyzing the character of the evaluation according to the ways of exterior lighting through the image prediction experiment by computer simulation. The aim of this research is to verify the validity of physical quantity & subjective evaluation on the basis of Online experiment. The following carried out the experiment procedure by conditions of Online experiment, 1) to make a photo of Online experirrent, 2) to measure physical quantity of luminance, and 3) to do subjective evaluation in Online experiment by means of vocabulary of the evaluation through preparation experiment. Then to verify the validity of Online and CG experiment, Online and photo experiment with each subjective evaluation results. The result of this study is that the validity difference is within 5% in the verification the validity of the physic amount, which showed little difference. While in verification of subjective evaluation of online and CG, online and photo experiment, the result is showed little difference as well except a little the item.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.73-80
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• 2006

Fingerprint-based verification system has been used for a very long time. Because of their well-known uniqueness and immutability, fingerprint is one of the most widely used biometric features. However, fingerprint identification system has such a critical weakness that the performance of verification is reduced drastically for a poor input fingerprint. In this paper, an image enhancement algorithm using enhanced direction and enhanced binary and aiming image is used to mitigate the problem in the preprocessing. The goal of image enhancement is to estimate the quality of input fingerprint image and to improve the clarity of ridge and valley structures of input fingerprint image. Also, a ridge orientation extraction method using index table is proposed to improve the speed of verification. It is shown by the experiments that proposed fingerprint verification system improves the minutiae extraction accuracy and performance of verification.

• Journal of Korean Society of Rural Planning
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• v.22 no.2
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• pp.141-152
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• 2016

The role of rural towns as a leisure space has recently been increasing with changes in the consumption trends in domestic tourism. Based on the tourists visiting the town of Sunheul-ri, Jocheon-eup, a rural Village in Jeju Island, this study categorized the market according to the images formed by the tourists of rural towns, and analyzed the preferred mode of participation in rural field activities for each category. We analyzed the characteristic factors of the images of rural tourism formed by the tourists, extracted three factors for cluster analysis, and then formed three groups: "Group of Rural Experience Activity" "Group of Rural Environment and Service" and "Group of Rest in the Rural" After analyzing the preferred activity in each image-category group, we found no significant differences among the groups in ordinary activities such as viewing the scenery, experiencing and learning about the natural environment, and culinary experiences. However, there were significant differences among the groups regarding participation in experiential tour programs with the purpose of active tourism. The "Group of Rural Experience Activity" sought to actively participate in various activity programs, whereas the "Group of Rest in the Rural" comparatively had a weaker preference for such active programs. We thus learnt that tourists' preferred activities are different according to the types of images formed by the tourists visiting rural towns. Therefore, to strengthen the competitive advantage of the rural tourist destinations of Jeju Island, it is necessary to provide various activity programs that are appropriate for the rural regions of Jeju and to accord with the expectations associated with each market segment category by positioning the programs according to the characteristics of the images held by the tourists.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.274-276
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• 2016

Recently due to increase of tobacco users, many problems have been issued. Not only smoking in public places, smoking indoors as well causes harm to non-smoking people. Smoking booths that are installed but the quality is considerably less and purification devices are not correctly installed, which leads to harm the people around the smoking booth. In this paper, we introduce the "Augmented Reality Billboard" in order for smokers to effectively recognize the non-smoking warning image and healthy warning messages, Kinect Camera Sensor and Augmented Reality (AR) functions are used to recognize the motion of a person to coordinate the corresponding coordinate values.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.13-21
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• 2019

The content based on image retrieval makes use of features of information within image such as color, texture and share for Retrieval data. we present a novel approach for improving retrieval accuracy based on DCT Filter-Bank. First, we perform DCT on a given image, and generate a Filter-Bank using the DCT coefficients for each color channel. In this step, DC and the limited number of AC coefficients are used. Next, a feature vector is obtained from the histogram of the quantized DC coefficients. Then, AC coefficients in the Filter-Bank are separated into three main groups indicating horizontal, vertical, and diagonal edge directions, respectively, according to their spatial-frequency properties. Each directional group creates its histogram after employing Otsu binarization technique. Finally, we project each histogram on the horizontal and vertical axes, and generate a feature vector for each group. The computed DC and AC feature vectors bins are concatenated, and it is used in the similarity checking procedure. We experimented using 1,000 databases, and as a result, this approach outperformed the old retrieval method which used color information.