• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.123-131
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• 2016

To capture color and near-infrared images simultaneously, a multi-spectral filter array(MSFA) sensor is used. This is because an NIR band gives additional invisible information to human eyes to see subject under extremely low light level. However, because lenses have different refractive indices for different wavelengths, lenses may fail to focus widely different rays to the same convergence point. This is why a chromatic aberration(CA) problem occurs and images are degraded. In this paper, the image restoration algorithm for an MSFA image, which removes the CA problem, is presented. The obtained MSFA image is filtered by the estimated low-pass kernel to generate a base image. This base image is used to remove CA problem in multi-spectral(MS) images. By modeling the image degradation process and by using the least squares approach of the difference between the high-frequencies of the base and MS images, the desired high-resolution MS images are reconstructed. The experimental results show that the proposed algorithm performs well in estimating the high-quality MS images and reducing the chromatic aberration problem.

• Journal of IKEEE
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• v.19 no.1
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• pp.64-72
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• 2015

In this paper, we have developed the gantry automation system via information technology (IT) to improve the productivity of fuel filter manufacturing process. The monitoring system of manufacturing process plays an important role in analyzing the defective products as well as improving the production yield rate. The experimental results of 3 months with 10000 samples validate that the error rate is decreased from 0.65 % to 0.45 %. Also, the defect of raw material is decreased via monitoring of material tools which can notify the time for replacement and accurate insertion of raw materials to the loader. The productivity is increased by reducing the process time from 94.7 sec to 78.8 sec per raw material through comparing the whole manufacturing courses : from inserting of raw material to outcome of product. The process time is decreased by 20.2 % by automation of inserting and outcome course. Moreover, safety of worker as well as reduction of transfer time are highly related with increase of productivity.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.79-84
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• 1996

In this paper, adaptive correlator model using backpropagation neural network based on complex multilayer perceptron is presented for suppressing interference of narrow-band of direct sequence spread spectrum receiver in CDMA mobile communication systems. Recursive least square backpropagation algorithm with backpropagation error is used for fast convergence and better performance in adaptive correlator scheme. According to signal noise ratio and transmission power ratio, computer simulation results show that bit error ratio of adaptive correlator uswing backpropagation neural network improved than that of adaptive transversal filter of direct sequence spread spectrum considering of co-channel and narrow-band interference. Bit error ratio of adaptive correlator using backpropagation neural network is reduced about $10^{-1}$ than that of adaptive transversal filter where interference versus signal ratio is 5 dB.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.675-682
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• 2014

Prostate is only an organ of men. To diagnose the disease of the prostate, generally transrectal ultrasound(TRUS) images are used. Detecting its boundary is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Support Vector Machine(SVM) is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing. Gabor filter bank for extraction of rotation-invariant texture features has been implemented. SVM for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted. A number of experiments are conducted to validate this method and results shows that the proposed algorithm extracted the prostate boundary with less than 10% relative to boundary provided manually by doctors.

• Journal of Digital Convergence
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• v.18 no.9
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• pp.363-371
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• 2020

This study based on the digital innovation of the fashion industry has researched digital-based face design that already has many users all over the world through social media and has influenced the fashion industry. The purpose of this study is to present the future vision of the direction of the fashion industry by classifying representative cases of augmented reality-based digital face design and deriving the oriented value that penetrates them. It was needed to analyzing 3D designer's works that provide digital filter-based face design to the public through Instagram and Facebook. As a result of observing the oriented value of digital face design from the point of view of modern fashion through case exploration, three trends were drawn: experimental formativeness orientation, playful experience orientation, and future technology orientation. This study limited the scope to digital-based face design, but the conclusions presented through these are applicable to all areas of fashion. Therefore, it is supposed to expect to study new phenomena related to fashion design and fashion communication based on digital augmented reality beyond the scope of face design in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1C
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• pp.82-91
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• 2005

This paper introduces an efficient affine projection algorithm(APA) using iterative hyperplane projection. Among various fast converging adaptation algorithms, APA has been preferred to be employed for various applications due to its inherent effectiveness against the rank deficient problem. However, the amount of complexity of the conventional APA could not be negligible because of the accomplishment of sample matrix inversion(SMI). Moreover, the 'shifting invariance property' usually exploited in single channel case does not hold for the application of space-time decision-directed equalizer(STDE) deployed in single-input-multi-output(SIMO) systems. Thus, it is impossible to utilize the fast adaptation schemes such as fast transversal filter(FlF) having low-complexity. To accomplish such tasks, this paper introduces the low-complexity APA by employing hyperplane projection algorithm, which shows the excellent tracking capability as well as the fast convergence. In order to confirm th validity of the proposed method, its performance is evaluated under wireless SIMO channel in respect to bit error rate(BER) behavior and computational complexity.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.225-236
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• 2013

The voice recognition has been made continuously. Now, this technology could support even natural language beyond recognition of isolated words. Interests for the voice recognition was boosting after the Siri, I-phone based voice recognition software, was presented in 2010. There are some occasions implemented voice enabled services using Korean voice recognition softwares, but their accuracy isn't accurate enough, because of background noise and lack of control on voice related features. In this paper, we propose a sort of multi-purpose preprocessor to improve this situation. This supports Keyword spotting in the continuous speech in addition to noise filtering function. This should be independent of any voice recognition software and it can extend its functionality to support continuous speech by additionally identifying the pre-predicate and the post-predicate in relative to the spotted keyword. We get validation about noise filter effectiveness, keyword recognition rate, continuous speech recognition rate by experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.219-230
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• 2017

This paper proposes a vehicle to road tracking algorithm based on vision sensor by using EKF(Extended Kalman Filter). The lateral offset, heading angle, and curvature which are obtained from vehicle to road tracking might be used as inputs to steering controller of LKAS(Lane Keeping Assist System) or for the warning decision logic of LDWS(Lane Departure Warning System). To the end, in this paper, the yaw rate, steering angle, and vehicle speed as well as lane raw points together with considering of vehicle lateral dynamics are utilized to improve the exactness and convergence of the vehicle to road tracking. The proposed algorithm has been tested at a proving ground that consists of straight and curve sections and compared with GPS datum using DGPS-RTK equipment to show the feasibility of the proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1083-1088
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• 2014

Recently, due to advances in both imaging technology and ICT, various types of image processing services became available and the application services of these two technologies are diversifying. Recognition of vehicle license plates is used in places where vehicle information is needed such as in parking management. However, existing systems have economic disadvantages like issuing parking tickets and attaching unnecessary equipment. In order to solve these problems, we designed and implemented automatic parking management system through recognition of vehicle license plates by using emguCV that is based on OpenCV. Additionally, we designed improved UI to handle the entire parking management situation which include information such as details of each parking vehicle, parking time and remaining parking spaces without screen movement. This improved UI is implemented with the use of WPF which is the latest technology in user program development. The emguCV used in this paper showed the most optimized performance in Intel based environment. With it, we obtained the result of within 0.5 seconds of recognition processing time and over 90% of recognition rate. Through improved UI, the manager could both simply and intuitively manage the entire system.

• KSCI Review
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• v.14 no.1
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• pp.241-248
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• 2006

The recognition of a relatively big and rarely movable object. such as refrigerator and air conditioner, etc. is necessary because these objects can be crucial global stable features of Simultaneous Localization and Map building(SLAM) in the indoor environment. In this paper. we propose a novel method to recognize these big objects using a sequence of 3D scenes. The particles representing an object to be recognized are scattered to the environment and then the probability of each particles is calculated by the matching test with 3D lines of the environment. Based on the probability and degree of convergence of particles, we can recognize the object in the environment and the pose of object is also estimated. The experimental results show the feasibility of incremental object recognition based on particle filtering and the application to SLAM