• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.97-105
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• 2020

Recently, for a smart city, there is a demand for a technology for acquiring traffic information using an intelligent road infrastructure and managing it. In the meantime, various technologies such as loop detectors, ultrasonic detectors, and image detectors have been used to analyze road traffic information but these have difficulty in collecting various informations, such as traffic density and length of a queue required for building a traffic information DB for moving vehicles. Therefore, in this paper, assuming a smart city built on the basis of a camera infrastructure such as intelligent CCTV on the road, a solution for calculating the traffic DB of moving vehicles using Vision Tracking of road CCTV cameras is presented. Simulation and verification of basic performance were conducted and solution can be usefully utilized in related fields as a new intelligent traffic DB calculation solution that reflects the environment of road-mounted CCTV cameras and moving vehicles in a variable smart city road environment. It is expected to be there.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.107-116
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• 2015

In compliance with digital device growth, the proliferation of high-tech computers, the availability of high quality and inexpensive video cameras, the demands for automated video analysis is increasing, especially in field of intelligent monitor system, video compression and robot vision. That is why object tracking of computer vision comes into the spotlight. Tracking is the process of locating a moving object over time using a camera. The consideration of object's scale, rotation and shape deformation is the most important thing in robust object tracking. In this paper, we propose a robust object tracking scheme using Random Forest. Specifically, an object detection scheme based on region covariance and ZNCC(zeros mean normalized cross correlation) is adopted for estimating accurate object location. Next, the detected region will be divided into five regions for random forest-based learning. The five regions are verified by random forest. The verified regions are put into the model pool. Finally, the input model is updated for the object location correction when the region does not contain the object. The experiments shows that the proposed method produces better accurate performance with respect to object location than the existing methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.35-44
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• 2012

Most recent infrared (IR) sensors have a focal-plane array (FPA) structure. Spatial non-uniformity of a FPA structure, however, introduces unwanted fixed pattern noise (FPN) to images. This non-uniformity correction (NUC) of a FPA can be categorized into target-based and scene-based approaches. In a target-based approach, FPN can be separated by using a uniform target such as a black body. Since the detector response randomly drifts along the time axis, however, several scene-based algorithms on the basis of a video sequence have been proposed. Among those algorithms, the state-of-the-art one based on Kalman filter uses one-directional warping for motion compensation and only compensates for offset non-uniformity of IR camera detectors. The system model using one-directional warping cannot correct the boundary region where a new scene is being introduced in the next video frame. Furthermore, offset-only correction approaches may not completely remove the FPN in images if it is considerably affected by gain non-uniformity. Therefore, for FPN reduction in IR videos, we propose a joint correction algorithm of gain and offset based on bi-directional warping. Experiment results using simulated and real IR videos show that the proposed scheme can provide better performance compared with the state-of-the art in FPN reduction.

• Journal of IKEEE
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• v.24 no.1
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• pp.302-310
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• 2020

In this paper, we have implemented the living waste analysis system based on IoT and AI(Artificial Intelligence), and proposed effective waste process and management method. The Jeju location have the strong point to devise a stratagem and estimate waste quantization, rather than others. Especially, we can recognized the amount variation of waste to the residence people compare to the sightseer number, and the good example a specific waste duty. Thus this paper have developed the IoT device for interconnecting the existed CCTV camera, and use the AI algorithm to analysis the waste image. By using these decision of image analysis, we can inform their deal commend and a decided information to the map of the waste cars. In order to evaluate the performance of IoT, we have experimented the electromagnetic compatibility under a national official authorization KN-32, KN61000-4-2~6, and obtained the stable experimental results. In the further experimental results, we can applicable for an data structure for precise definition command by using the simulated several waste image with artificial intelligence algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.3
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• pp.255-263
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• 2014

Today, a number of CCTV on the highway is to observe the flow of traffics. There have been a number of studies where traffic data (e.g., the speed of vehicles and the amount of traffic on the road) are transferred back to the centralized server so that an appropriate action can be taken. This paper introduces a system that detects the changes of traffic flows caused by an accident or unexpected stopping (i.e., vehicle remains idle) by monitoring each lane separately. The traffic flows of each lane are level spacing curve that shows Wigner distribution for location vector. Applying calogero-moser system and Hamiltonian system, probability equation for each level-spacing curve is derived. The high level of modification of the signal means that the lane is in accident situation. This is different from previous studies in that it does more than looking for the signal from only one lane, now it is able to detect an accident in entire flow of traffic. In process of monitoring traffic flow of each lane, when camera recognizes a shadow of vehicle as a vehicle, it will affect the accident detecting capability. To prevent this from happening, the study introduces how to get rid of such shadow. The system using Basian network method is being compared for capability evaluation of the system of the study. As a result, the system of the study appeared to be better in performance in detecting the modification of traffic flow caused by idle vehicle.

• Spatial Information Research
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• v.12 no.2
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• pp.181-191
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• 2004

Nowadays, GPS-photogrammetry can be applied to the basemap production, a land register and NGIS. And from now on, as the increase of GPS receiver rate, the study on the interpolation methods considering the exact movement of an aircraft at photoflight and the study on the supplement of GPS defect by INS are required continuously. GPS-Photogrammetry, which are based on the direct measurement of the projection centers and attitude at the moment of camera exposure time through loading the GPS receiver in aircraft. This photogrammetric methods can of for us to acquire the exterior orientation parameters with only minimum ground control points, even the ground control process could be completely skipped. Consequently, we can drastically reduce the time and cost far the mapping process. In this thesis, two test flights were conducted in area to evaluate the performance of accuracy and efficiency through the analysis of results between the two photogrammetric methods, that is, traditional photograrammetry, GPS-Photogrammetry. Test results shows that a large variety of advantages of GPS-Photogrammetry against traditional photogrammetry is to be verified. Especially, the number of ground control points for the exterior orientation could be saved more than 70～80%, and the cost far map production 30～50%, respectively. In addition, it was convinced that the large reduction of control points has not any effect on the block accuracy.

• Korean Journal of Optics and Photonics
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• v.26 no.1
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• pp.23-29
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• 2015

In this paper, we propose a microscope system for detecting both a tumor and blood vessels in brain tumor surgery as fluorescence images by using multiple light sources and a beam-splitter module. The proposed method displays fluorescent images of the tumor and blood vessels on the same display device and also provides accurate information about them to the operator. To acquire a fluorescence image, we utilized 5-ALA (5-aminolevulinic acid) for the tumor and ICG (Indocyanine green) for blood vessels, and we used a beam-splitter module combined with a microscope for simultaneous detection of both. The beam-splitter module showed the best performance at 600 nm for 5-ALA and above 800 nm for ICG. The beam-splitter is flexible to enable diverse objective setups and designed to mount a filter easily, so beam-splitter and filter can be changed as needed, and other fluorescent dyes besides 5-ALA and ICG are available. The fluorescent images of the tumor and the blood vessels can be displayed on the same monitor through the beam-splitter module with a CCD camera. For ICG, a CCD that can detect the near-infrared region is needed. This system provides the acquired fluorescent image to an operator in real time, matching it to the original image through a similarity transform.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.221-228
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• 2014

The color and shape of the tongue reflect the physiological and clinico-pathological condition of the body. Recently, various tongue image acquisition devices have been developed for accurate diagnosis based on quantitative and objective tongue features. Since a color information is essential for tongue diagnosis, the performance of an illuminator is very important for the tongue image acquisition device. In this study, we developed an indirect illumination, which is possible to improve a homogeneity of light intensities on the tongue surface, and evaluated its performances. In order to realize the indirect illumination (II), a semi-ellipsoidal solid structure (SESS) for the light reflex was located in the system, and two high-brightness white LEDs were placed for illuminating the areas under frontal camera in the SESS. The tongue surface was illuminated by reflected light from the SESS. The light homogeneity induced by three different illuminations including the II was evaluated by calculating coefficient of variation (CV) of illuminance of five regions. The II showed less than 0.01 of CV and the direct illumination (DI) and the direct illumination with a light diffusion plate (DILDP) showed 0.16 and 0.13, respectively. The reflexed pixel ratios of tongue phantom images show 5.76%, 4.22%, 1.79% for the DI, the DILDP and the II, respectively. The homogeneity of a tongue phantom was evaluated by calculating CV of mean pixel values of six different tongue regions, and showed less than 0.06 in the II. If the II technique apply to tongue diagnosis system, it is expected to improve diagnostic accuracy in clinic.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.