• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.61-65
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• 2011

Recently, LCD (liquid crystal display) industry is needed to goods of high reliability and wide range temperature condition and it is interested in products for extremely cold condition without failure of light-up. In this experiment, we made the LED backlight unit for Automotive-navigation under the extremely cold condition. And for making this backlight unit, we used to eight side emitting type white LEDs with 3W high power LED. We could know that this backlight unit releases to 18,000 nit in 24W power consumption and start up voltage time is under the 1ms in the ambient temperature at -40.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3148-3154
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• 2000

In this paper. the design and implementationof the on-line registration system for the school affairs is described. The environments for the system configurations include a PC server under Linux Iperating System. Apache Web-server, and MySQL as database engine. In addition, PHP, which becomes a popular Internet server-based script language lately, is used to implement a real-time database. In order to avoid overload problems during short-term registration period, which deconstraces the typical surge of traffics, the proposed system is designed to minimize the unnecessary interfacing tasks. On administrator side task, the sytem is designed to have environments by separating the dechcated server that restricts the scope of specific database thasks. In doing so, it become possibal to build an optical system by distributing, balancing the transaction load, maintainimg the security and efficient administrative tasks.

• Journal of Internet Computing and Services
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• v.5 no.2
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• pp.41-47
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• 2004

Recently, motion capture has become one of the most promising technologies in animation. Realistic motion data can be captured by recording the movement of a real actor with an optical or magnetic motion capture system. This paper deals with motion editing by a geometric mean filter. Since the captured motion has some noises that cause a jerky motion, it needs a smoothing process to make it natural. A geometric mean filter is proposed to produce natural motions without jerky motions. Experimental results show that the geometric mean filter can effectively remove noises that cause a jerky motion and it can guarantee the most natural motions among various spatial filters. This method could be applied to the various fields such as real time animation, virtual reality applications, 3D applications, and etc.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.129-141
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• 2010

In this paper, we present a wearable intelligent device based on multi-sensor for monitoring human activity. In order to recognize multiple activities, we developed activity recognition algorithms utilizing an image sensor and a 3-axis accelerometer sensor. We proposed a grid?based optical flow method and used a SVM classifier to analyze data acquired from multi-sensor. We used the direction and the magnitude of motion vectors extracted from the image sensor. We computed the correlation between axes and the magnitude of the FFT with data extracted from the 3-axis accelerometer sensor. In the experimental results, we showed that the accuracy of activity recognition based on the only image sensor, the only 3-axis accelerometer sensor, and the proposed multi-sensor method was 55.57%, 89.97%, and 89.97% respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.269-276
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• 2018

OCR(Optical Character Recognition) using computers has been developed for 20 years and applied to various fields such as parking management based on the recognition of license plates of cars. This technology was also used in the development of our smart OCR-based household ledger. In order to improve filling the purchase history into a smartphone based household account book, we can take pictures of receipts with the smarphone camera and automatically organize the purchase list. In this process, the recognition rate of the characters of the receipt image is not high enough with OCR technology. We could improve the rate by applying the image processing technology and adjusting the contrast of the receipt image. The rate improved from 89% to 92.5%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5522-5540
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• 2018

Vehicular license plate (LP) recognition system has risen as a significant field of research recently because various explorations are currently being conducted by the researchers to cope with the challenges of LPs which include different illumination and angular situations. This research focused on restricted conditions such as using image of only one vehicle, stationary background, no angular adjustment of the skewed images. A real time vehicular LP recognition scheme is proposed for the skewed images for detection, segmentation and recognition of LP. In this research, a polar co-ordinate transformation procedure is implemented to adjust the skewed vehicular images. Besides that, window scanning procedure is utilized for the candidate localization that is based on the texture characteristics of the image. Then, connected component analysis (CCA) is implemented to the binary image for character segmentation where the pixels get connected in an eight-point neighbourhood process. Finally, optical character recognition is implemented for the recognition of the characters. For measuring the performance of this experiment, 300 skewed images of different illumination conditions with various tilt angles have been tested. The results show that proposed method able to achieve accuracy of 96.3% in localizing, 95.4% in segmenting and 94.2% in recognizing the LPs with an average localization time of 0.52s.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4443-4462
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• 2020

This paper proposes a new framework of reversible data hiding scheme for absolute moment truncation coding (AMBTC) compressed images. AMBTC-based RDH can be applied to optical remote sensing (ORS) image transmission, which achieves target region preservation and image compression simultaneously. Existing methods can be concluded as two types. In type I schemes, stego codes mimic the original AMBTC format where no file bloat occurs, yet the carried secret data is limited. Type II schemes utilize predication errors to recode quantity levels of AMBTC codes which achieves significant increase in embedding capacity. However, such recoding causes bloat inside stego format, which is not appropriate in mentioned ORS transmission. The proposed method is a novel type I RDH method which prevents bloat inside AMBTC stego codes with significant improvement in embedding capacity. The AMBTC compressed trios are grouped into two categories according to a given threshold. In smooth trio, the modified low quantity level is constructed by concatenating Huffman codes and secret bits. The reversible contrast mapping (RCM) is performed to complex trios for data embedment. Experiments show that the proposed scheme provides highest payload compared with existing type I methods. Meanwhile, no expansion inside stego codes is caused.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1193-1215
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• 2021

The measurement of the key product quality index plays an important role in improving the production efficiency and ensuring the safety of the enterprise. Since the actual working conditions and parameters will inevitably change to some extent with time, such as drift of working point, wear of equipment and temperature change, etc., these will lead to the degradation of the quality variable prediction model. To deal with this problem, the selective integrated moving windows based principal component regression (SIMV-PCR) is proposed in this study. In the algorithm of traditional moving window, only the latest local process information is used, and the global process information will not be enough. In order to make full use of the process information contained in the past windows, a set of local models with differences are selected through hypothesis testing theory. The significance levels of both T - test and χ² - test are used to judge whether there is identity between two local models. Then the models are integrated by Bayesian quality estimation to improve the accuracy of quality variable prediction. The effectiveness of the proposed adaptive soft measurement method is verified by a numerical example and a practical industrial process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1584-1596
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• 2022

According to a survey published in an authoritative journal in January 2020, the globalincidence rate of mental illness is 8.3% for men and 10.6% for women, which indicates thatmental illness has become a globally recognized obstacle. Therefore, specific psychotherapy including mental illness will become an important research topic. It is very effective forpatients with special mental diseases, such as mental illness, to reduce their mental reaction byexposure therapy; the system uses the virtual reality system of medical images processed by learningalgorithm to reproduce the effect of virtual reality exposure method of the high scene of transparent ladder. Compared with the old invasive exposure scene, the results show that theimprovement of both conditions has obvious effect, and the effect of human treatment underthe two conditions is not good. There are obvious differences, which show that virtual reality model will gradually replace the on-the-spot feeling. Finally, with more and more researchers have put forward a variety of other virtual reality image processing models, the research of image processing has gradually become more and more interested.