• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.307-314
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• 2017

Stick-PC is small and portable, So it can be used like a desktop if you connect it to a display device such as a monitor or TV anytime and anywhere. Accordingly, Stick-PC can related to various crimes, and various evidence may remain. Stick-PC uses the same Windows version of the operating system as the regular Desktop, the artifacts to be analyzed are the same. However, unlike the Desktop, it can be used as a meaningful information for forensic investigation if it is possible to identify the actual user and trace the usage by finding the traces of peripheral devices before analyzing the system due to the mobility. In this paper, We presents a method of collecting images using Bootable OS, which is one of the image collection methods of Stick-PC. In addition, we show how to analyze the trace of peripheral connection and network connection trace such as Display, Bluetooth through the registry and event log, and suggest the application method from the forensic point of view through experimental scenario.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.12-26
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• 2000

In this paper, we propose a post-processing algorithm to remove false minutiae which decrease the overall performance of an automatic fingerprint identification system by increasing computational complexity, FAR(False Acceptance Rate), and FRR(False Rejection Rate) in matching process. The proposed algorithm extracts candidate minutiae from thinned fingerprint image. Considering characteristics of the thinned fingerprint image, the algorithm selects the minutiae that may be false and located in recoverable area. If the area where the selected minutiae reside is thinned incorrectly due to noise and loss of information, the algorithm recovers the area and the selected minutiae are removed from the candidate minutiae list. By examining the ridge pattern of the block where the candidate minutiae are found, true minutiae are recovered and in contrast, false minutiae are filtered out. In an experiment, Fingerprint images from NIST special database 14 are tested and the result shows that the proposed algorithm reduces the false minutiae extraction rate remarkably and increases the overall performance of an automatic fingerprint identification system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1365-1373
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• 2002

In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance. This is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until recognize obstacle from input image that preprocessed by edge detection, converting, thresholding. And it could avoid the obstacle when recognize obstacle by line histogram intensity. Host PC measurement wave from various line histogram each 20 pixel. This histogram is (x, y) value of pixel. For example, first line histogram intensity wave from (0, 0) to (0, 197) and last wave from (280, 0) to (2n, 197. So we find uniform wave region and nonuniform wave region. The period of uniform wave is obstacle region. we guess that algorithm is very useful about moving robot for obstacle avoidance.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.12
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• pp.59-65
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• 2004

A stable reference voltage generator is necessary to the infrared image signal readout circuit(ROIC) to improve noise characteristics of signal originated from infrared devices, that is, to gain good images. In this paper, bandgap circuit operating at cryogenic temperature of 77K for Infrared image ROIC(readout integrated circuit) was first made. It demonstrates practical use possibility through taking measurements and estimations. Bandgap circuit is a representative voltage reference circuit. Most of bandgap reference circuits which are presented so far operate at room temperature, and their characteristic are not suitable for infrared image ROIC operating at liquid nitrogen temperature, 77K. To design bandgap circuit operating at cryogenic temperature, suitable circuit is selected and the parameter characteristics of used devices as temperature change are seen by a theoretical study and fitted at liquid temperature with considering such characteristics. This circuit has been fabricated in the Hynix 0.6um standard CMOS process, and the output voltage measured shows that the stability is 1.042±0.0015V over the temperature range of 60K to 110K and is better than bandgap circuits operated at room temperature.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.58-66
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• 2006

In this paper, we apply DCM(Dilation of Color and Motion information) mask and Active Contour Models(Snakes) to extract facial outline in moving pictures with complex background. First, we propose DCM mask which is made by applying morphology dilation and AND operation to combine facial color and motion information, and use this mask to detect facial region without complex background and to remove noise in image energy. Also, initial curves are automatically set according to rotational degree estimated with geometric ratio of facial elements to overcome the demerit of Active Contour Models which is sensitive to initial curves. And edge intensity and brightness are both used as image energy of snakes to extract contour at parts with weak edges. For experiments, we acquired total 480 frames with various head-poses of sixteen persons with both eyes shown by taking pictures in inner space and also by capturing broadcasting images. As a result, it showed that more elaborate facial contour is extracted at average processing time of 0.28 seconds when using interpolated initial curves according to facial rotation degree and using combined image energy of edge intensity and brightness.

• Journal of the Ergonomics Society of Korea
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• v.33 no.5
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• pp.395-405
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• 2014

Objective: The aim of this study is to investigate 1) somatotopic arrangement of the second and third fingers in SI area 2) difference of neural activation in the SI area produced by stimulation with different frequencies 3) correlation between the intensity of tactile perception by different stimulus intensity and the level of brain activation measurable by means of fMRI. Background: Somatosensory cortex can obtain the information of environmental stimuli about "where" (e.g., on the left palm), "what" (e.g., a book or a dog), and "how" (e.g., scrub gently or scrub roughly) to organism. However, compared to visual sense, the neural mechanism underlying the processing of specific electrotactile stimulus is still unknown. Method: 10 right-handed subjects participated in this study. Non-painful electrotactile stimuli were delivered to two different finger tips of right hand. Functional brain images were collected from 3.0T MRI using the single-shot EPI method. The scanning parameters were as follows: TR and TE were 3000, 35ms, respectively, flip angle 60, FOV $24{\times}24cm$, matrix size $64{\times}64$, slice thickness 4mm (no gap). SPM5 was used to analyze the fMRI data. Results: Significant activations produced by the stimulation were found in the SI, SII, the subcentral gyrus, the precentral gyrus, and the insula. In all participants, statistically significant activation was observed in the contralateral SI area and the bilateral SII areas by the stimulation on the fingers but ipsilaterally dominant. The SI area representing the second finger generally located in the more lateral and inferior side than that of the third finger across all the subjects. But no difference in brain area was found for the stimulation of the fingers by different frequencies. And two typical patterns were observed on the relationship between the perceived psychological intensity and the amount of voxels in the primary sensory cortex during the stimulation. Conclusion: It was possible to discriminate the representation sites in the SI by electrotactile stimulation of digit2 and digit3. But we could not find the differences of the brain areas according to different stimulation frequencies from 3 to 300Hz. Application: The results of the study can provide a deeper understanding of somatosensory cortex and offer the information for tactile display for blinds.

• Journal of Gifted/Talented Education
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• v.23 no.5
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• pp.637-648
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• 2013

The relationship between the cerebral cortex and human intelligence has been studied using various methods, and related brain areas involved in intellectual manifestation have been discovered individually. Such studies have also shown the cerebellum is closely involved in various cognitive functions such as language, memory, and information processing. However, studies showing an activity difference between the cerebral cortex and cerebellum when performing specific tasks are hard to find. This study searched and analyzed the active regions of the cerebral cortex and cerebellum seen while performing the inference of geometrical figures. A WAIS intelligence test was conducted using 81 healthy boys (16.3 years of age on average), and five categories were classified. While performing the inference of shapes, their brain images were taken using functional magnetic resonance imaging (fMRI). As a result, the activity in 12 brain regions was observed, including in the cerebral cortex, the bilateral inferior parietal, the visual cortex, bilateral superior parietal, frontal-Inf-Tri-R, and bilateral caudate, while activities in 5 discrete areas were seen in the cerebellum. In particular, the higher the intelligence (IQ) of the subject, the stronger their activity. Among those with the most superior intelligence, subjects with an IQ of 140-147 showed significantly higher activity compared to the other groups. Such results seem to represent a very high utilization of intelligence in a highly gifted group, and we can expect to use this to determine the super gifted.

• Journal of IKEEE
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• v.24 no.2
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• pp.529-535
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• 2020

As the main technology of the 4th industrial revolution, immersive 360-degree video contents are drawing attention. The market size of immersive 360-degree video contents worldwide is projected to increase from $6.7 billion in 2018 to approximately $70 billion in 2020. However, most of the immersive 360-degree video contents are distributed through illegal distribution networks such as Webhard and Torrent, and the damage caused by illegal reproduction is increasing. Existing 2D video industry uses copyright filtering technology to prevent such illegal distribution. The technical difficulties dealing with immersive 360-degree videos arise in that they require ultra-high quality pictures and have the characteristics containing images captured by two or more cameras merged in one image, which results in the creation of distortion regions. There are also technical limitations such as an increase in the amount of feature point data due to the ultra-high definition and the processing speed requirement. These consideration makes it difficult to use the same 2D filtering technology for 360-degree videos. To solve this problem, this paper suggests a feature point extraction and identification technique that select object identification areas excluding regions with severe distortion, recognize objects using deep learning technology in the identification areas, extract feature points using the identified object information. Compared with the previously proposed method of extracting feature points using stitching area for immersive contents, the proposed technique shows excellent performance gain.

• Spatial Information Research
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• v.18 no.4
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• pp.1-11
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• 2010

Unlike the previous studies which have focused on 2-dimensional urban characteristics, this paper presents statistical models explaining urban heat island(UHI) effect by 3-dimensional urban morphologic information and addresses its policy implications. 3~dimensional informations of Columbus, Ohio arc captured from LiDAR data and building boundary informations are extracted from a building digital map, Finally NDV[ and temperature data are calculated by manipulating band 3, band 4, and thermal hand of LandSat images. Through complicated data processing, 6 independent variables(building surface area, building volume, height to width ratio, porosity, plan surface area) are introduced in simple and multiple linear regression models. The regression models are specified by Box-Tidwell method, finding the power to which the independent variable needs to raised to be in a linearity. Porosity, NDVI, and building surface area are carefully chosen as explanatory variables in the final multiple regression model, which explaining about 57% of the variability in temperatures. On reducing UHI, various implications of the results give guidelines to policy-making in open space, roof garden, and vertical garden management.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.35-43
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• 2010

1D PCA utilized in the face appearance-based face recognition methods such as eigenface-based face recognition method may lead to less face representative power and more computational cost due to the resulting 1D face appearance data vector of high dimensionality. To resolve such problems of 1D PCA, 2D PCA-based face recognition methods had been developed. However, the face representation model obtained by direct application of 2D PCA to a face image set includes both face common features and face distinctive identity features. Face common features not only prevent face recognizability but also cause more computational cost. In this paper, we first develope a model of a face distinctive identity feature subspace separated from the effects of face common features in the face feature space obtained by application of 2D PCA analysis. Then, a novel robust face recognition based on the face distinctive identity feature subspace model is proposed. The proposed face recognition method based on the face distinctive identity feature subspace shows better performance than the conventional PCA-based methods (1D PCA-based one and 2D PCA-based one) with respect to recognition rate and processing time since it depends only on the face distinctive identity features. This is verified through various experiments using Yale A and IMM face database consisting of face images with various face poses under various illumination conditions.