• IEIE Transactions on Smart Processing and Computing
• /
• v.6 no.4
• /
• pp.262-268
• /
• 2017

Intelligent video surveillance systems have been developed to monitor global areas and find specific target objects using a large-scale database. However, person re-identification presents some challenges, such as pose change and occlusions. To solve the problems, this paper presents an improved person re-identification method using sparse representation and saliency-based dictionary construction. The proposed method consists of three parts: i) feature description based on salient colors and textures for dictionary elements, ii) orthogonal atom selection using cosine similarity to deal with pose and viewpoint change, and iii) measurement of reconstruction error to rank the gallery corresponding a probe object. The proposed method provides good performance, since robust descriptors used as a dictionary atom are generated by weighting some salient features, and dictionary atoms are selected by reducing excessive redundancy causing low accuracy. Therefore, the proposed method can be applied in a large scale-database surveillance system to search for a specific object.

• The KIPS Transactions:PartB
• /
• v.13B no.1 s.104
• /
• pp.7-14
• /
• 2006

This paper presents an efficient face recognition method using both first moment of image and basis images. First moment which is a method for finding centroid of image, is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. Basis images which are the face features, are respectively extracted by principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). This is to improve the recognition performance by excluding the redundancy considering to second- and higher-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 48 face images(12 persons*4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed methods has a superior recognition performances(speed, rate) than conventional PCA and FP-ICA without preprocessing, the proposed FP-ICA has also better performance than the proposed PCA. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of Korea Multimedia Society
• /
• v.9 no.1
• /
• pp.33-40
• /
• 2006

This paper presents an efficient face recognition method using both first moment of image and eigenvector. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shitting to the centroid of face image. Eigenvector which are the basis images as face features, is extracted by principal component analysis(PCA). This is to improve the recognition performance by excluding the redundancy considering to second-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 60 face images(15 persons *4 scenes) of 320*243 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. In case of the 45 face images, the experimental results show that the recognition rate of the proposed methods is about 1.6 times and its the classification is about 5.6 times higher than conventional PCA without preprocessing. The city-block has been relatively achieved more an accurate classification than Euclidean or negative angle.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.4
• /
• pp.490-498
• /
• 1993

A variety of methods for measuring the velocity from an image sequence use the relationship between the spatial and temporal gradients of image brightness function. In most situations, an additional constraint is required because the velocity is not determined uniquely by a above relationship. Horn and Schunch proposed a constraint that the velocity field should vary smoothly over the image. This requirement, however, forces the velocity field to vary smoothly even across motion boundaries. To complement this probe, Nagel introduced and 'oriented smoothness' constraint which restricts variations of velocity field only in directions with small or no variation of image brightness function. On the other hand, Paquin and Dubois proposed a different type of constraint that the velocity is constant in a small area of image. But, this constraint also creates difficulties at motion boundaries which large variations in velocity field often occur. We propose the method to overcome these difficulties by utilizing the information of discontinuities in image brightness function, and present the experimental results.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.3
• /
• pp.139-146
• /
• 2004

A 2D/3D complex optical system and its vision inspection algerian is proposed and implemented as a single probe system for high speed, precise vision inspection of the solder pastes. One pass un length labeling algorithm is proposed instead of the conventional two pass labeling algorithm for fast extraction of the 2D shape of the solder paste image from the recent line-scan camera as well as the conventional area-scan camera, and the optical probe path generation is also proposed for the efficient 2D/3D inspection. The Moire interferometry-based phase shift algerian and its optical system implementation is introduced, instead of the conventional laser slit-beam method, for the high precision 3D vision inspection. All of the time-critical algorithms are MMX SIMD parallel-coded for further speedup. The proposed system is implemented for simultaneous 2D/3D inspection of 10mm${\times}$10mm FOV with resolutions of 10 ${\mu}{\textrm}{m}$ for both x, y axis and 1 ${\mu}{\textrm}{m}$ for z axis. Experiments conducted on several nBs show that the 2D/3D inspection of an FOV, excluding an image capturing, results in high speed of about 0.011sec/0.01sec, respectively, after image capturing, with $\pm$1${\mu}{\textrm}{m}$ height accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.6
• /
• pp.110-123
• /
• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Journal of the Korean Society of Radiology
• /
• v.10 no.4
• /
• pp.247-253
• /
• 2016

Ultrasound devices diagnose many disease, which is widely used, can not be standardized quantitative evaluated in order to evaluate sonography image of quality. Therefore, in this papers, aims to get correct image in order to accurate diagnosis by figuring out the appropriate parameter based on each target by measuring distortion which results in the analyzation of the sensitivity of SNR and the histogram of signal by manipulating parameter of 8 mm target in ATS-539 multipurpose phantom. Equipment using Acuson sequoia 512, convex probe and utilizes multi-objective phantom. experiment method is that first you put the phantom on the flat and acquire 85 sheets of image, changing frequency(2,3,4 MHz, harmonic 3, 4, 4.5 MHz), Focus(2, 4, 6 unit), and Dynamic Range(58, 68, 78, 88, 98) for a 8 mm structure. through the Image J program. The sensitivity angle of 8mm target through Image J program is gauged by each separate target SNR and the distorted angle subtract and measure Histogram of background from Histogram of signal and take top 40% from the given result value above. According to parameter variation we found out proper parameter by acquiring SNR of sensitivity and distortion data for aspect of transition. The more this findings have Focus, the lower distortion value and at 4 MHz frequency this result have high SNR and low distortion value. Dynamic Range got an appropriate image on 88 and 98. It is considered on the basis of the experimental data, the probability of disease diagnosis will get higher.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.35 no.5
• /
• pp.299-306
• /
• 2015

A conventional phased array system can control an ultrasonic beam electronically by adjusting the excitation time delay of individual elements in a multi-element probe and produce an ultrasonic image. In Contrast, full matrix capture (FMC) is a data acquisition process that allows receiving ultrasonic signals from one single shot of the phased array transducer element through all the other elements and captures the complete dataset from every possible transmit-receive combination. This FMC data can be used to create the ultrasonic image in post processing. It is possible to produce not only images equivalent to conventional phased array image but also total focusing method (TFM) images with improved resolution and sharpness, which is virtually focused at any point in a region of interest. In this paper, the system that can perform FMC by using a conventional phased array instrument is developed, and a study was conducted on the imaging algorithms to reconstruct sector B-scan and TFM images from FMC dataset.

• Transactions of the Korean hydrogen and new energy society
• /
• v.28 no.5
• /
• pp.521-530
• /
• 2017

Improving the microstructure of NiO/YSZ is one of several approaches used to enhance the electrical and mechanical properties of an anode support in Solid Oxide Fuel Cells (SOFCs). The aim of the work reported in this paper was to predict the relationship between these microstructural changes and the resulting properties. To this end, modification of the anode microstructure was carried out using different sizes of Poly (Methyl Methacrylate) (PMMA) beads as a pore former. The electrical conductivity and mechanical strength of these samples were measured using four-probe DC, and three-point bend-test methods, respectively. Thermal etching followed by high resolution SEM imaging was performed for sintered samples to distinguish between the three phases (NiO, YSZ, and pores). Recently developed image analysis techniques were modified and used to calculate the porosity and the contiguity of different phases of the anode support. Image analysis results were verified by comparison with the porosity values determined from mercury porosimetry measurements. Contiguity of the three phases was then compared with data from electrical and mechanical measurements. A linear relationship was obtained between the contiguity data determined from image analysis, and the electrical and mechanical properties found experimentally. Based upon these relationships we can predict the electrical and mechanical properties of SOFC support from the SEM images.

• Journal of Space Technology and Applications
• /
• v.1 no.1
• /
• pp.49-63
• /
• 2021

The exploration of the solar system is carried out through various payloads, and accordingly, many research results are emerging. We tried to apply deep-learning as a method of studying the bodies of solar system. Unlike Earth observation satellite data, the data of solar system differ greatly from celestial bodies to probes and to payloads of each probe. Therefore, it may be difficult to apply it to various data with the deep-learning model, but we expect that it will be able to reduce human errors or compensate for missing parts. We have implemented a model that detects craters on the lunar surface. A model was created using the Lunar Reconnaissance Orbiter Camera (LROC) image and the provided shapefile as input values, and applied to the lunar surface image. Although the result was not satisfactory, it will be applied to the image of the permanently shadow regions of the Moon, which is finally acquired by ShadowCam through image pre-processing and model modification. In addition, by attempting to apply it to Ceres and Mercury, which have similar the lunar surface, it is intended to suggest that deep-learning is another method for the study of the solar system.