• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.383-389
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• 2016

This paper presents a novel automatic white balance (AWB) algorithm for consumer imaging devices. While existing AWB methods require reference white patches to correct color, the proposed method performs the AWB function using only an input image in two steps: i) white point detection, and ii) color constancy gain computation. Based on the dark channel prior assumption, a white point or region can be accurately extracted, because the intensity of a sufficiently bright achromatic region is higher than that of other regions in all color channels. In order to finally correct the color, the proposed method computes color constancy gain values based on the Y component in the XYZ color space. Experimental results show that the proposed method gives better color-corrected images than recent existing methods. Moreover, the proposed method is suitable for real-time implementation, since it does not need a frame memory for iterative optimization. As a result, it can be applied to various consumer imaging devices, including mobile phone cameras, compact digital cameras, and computational cameras with coded color.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.2
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• pp.180-187
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• 2010

In this paper, a global path generation method is suggested using multiple grid maps connected with the mission type of unmanned combat vehicle(UCV). In order to carry out a mission for UCV, it is essential to find a global path which is coincident with the characteristics of the mission. This can be done by considering various combat circumstances represented as grid maps such as velocity map, threat map and communication map. Cost functions of multiple grid maps are linearly combined and normalized to them simultaneously for the path generation. The proposed method is realized using $A^*$, a well known search algorithm, and cost functions are normalized in the ratio of the traverse time which is one of critical information should be provided with the operators using the velocity map. By the experiments, it is checked found global paths match with the mission type by reflecting input data of grid maps properly and the computation time is short enough to regenerate paths in real time as combat circumstances change.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.120-126
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• 2020

Studies are being conducted regarding falling recognition using sensors on smartphonesto recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.414-422
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• 2002

In this paper, we propose a new method of adaptive neuro-fuzzy control using CFCM(Conditional Fuzzy c-means) clustering and fuzzy equalization method to deal with adaptive control problem. First, in the off-line design, CFCM clustering performs structure identification of adaptive neuro-fuzzy control with the homogeneous properties of the given input and output data. The parameter identification are established by hybrid learning using back-propagation algorithm and RLSE(Recursive Least Square Estimate). In the on-line design, the premise and consequent parameters are tuned to RLSE with forgetting factor due to a characteristic of time variant. Finally, we applied the proposed method to the water temperature control system and obtained better results than previous works such as fuzzy control.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1968-1971
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• 2003

We propose a knowledge-based algorithm for extracting an object boundary from low-quality image like the forward looking infrared image. With the multi-classes training data set, the global shape is modeled by multispace KL(MKL)[1] and curvature model. And the objective function for fitting the deformable boundary template represented by the shape model to true boundary in an input image is formulated by Bales rule. Simulation results show that our method has more accurateness in case of multi-classes training set and performs better in the sense of computation cost than point distribution model(PDM)[2]. It works well in distortion under the noise, pose variation and some kinds of occlusions.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.4
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• pp.17-29
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• 1999

This paper presents a high level synthesis method targeting low power consumption for data-dominated CMOS circuits (e.g., DSP). The high level synthesis is divided into three basic tasks: scheduling, resource and register allocation. For lower power scheduling, we increase the possibility of reusing an input operand of functional units. For a scheduled data flow graph, a compatibility graph for register and resource allocation is formed, and then a special weighted network is then constructed from the compatibility graph and the minimum cost flow algorithm is performed on the network to obtain the minimum power consumption data path assignment. The formulated problem is then solved optimally in polynomial time. This method reduces both the switching activity and the capacitance in synthesized data path. Experimental results show 15% power reduction in benchmark circuits.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.40-47
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• 2006

This paper introduces an efficient CRC logic partitioning algorithm to design pipelined parallel CRC circuits aimed at improving speed performance. Focusing on the cases that the input data width is greater than the polynomial degree, equations are derived to divide the parallel CRC logic and decide the length of the pipeline stage. Through design experiments on different types of parallel CRC circuits, we have found a significant reduction in delay by adopting our approach.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.509-520
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• 2003

In this paper, we developed a new and robust algorithm for a practical and very efficient MPEG-4 video coding. The MPEG-4 video group has developed the video Verification Model(VM) which evolved through time by means of core experiments. And in the standardization process, MS-FDAM was developed based on the standard document of ISO/IEC 14496-2 and VM as a reference MPEG-4 coding system. But MS -FDAM has drawbacks in practical MPEG-4 coding and it does not have the VOP extraction functionality. In this research, we implemented a preprocessing system for a real-time input and the VOP extraction for a practical content-based MPEG-4 video coding and also implemented the motion detection to achieve the high compression rate of 180:1.

• Journal of KIISE:Software and Applications
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• v.34 no.8
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• pp.743-751
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• 2007

Model checking has been successfully applied to hardware verification. Software is more subtle than hardware with respect to formal verification due to its infinite state space. Although there are many research activities in this area, bounded model checking is regarded as a promising technique. Bounded model checking uses an upper bound to unroll its model, which is the main advantage of bounded model checking compared to other model checking techniques. In this paper, we applied bounded model checking to verify BIR which is the input model for the model checking tool BOGOR. Some BIR examples are verified with our technique. Experimental results show that bounded model checking is better than explicit model checking provided by BOGOR. This paper presents the formalization of BIR and the encoding algorithm of BIR into CNF.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.455-458
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• 1997

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are no quantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by visual stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. Seven university students were participated in this study. The experiment was devised with eleven experimental conditions, which are control and ten different types of visual stimulation based on IAPS (International Affective Picture Systems). Wavelet transformation was employed to analyze the EEG signals. Most positive and negative emotional response were compared in pairs. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with positive and negative stimulus were found. This study could be extended to establish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.