• Journal of Game and Entertainment
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• v.2 no.2
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• pp.45-50
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• 2006

In a face detection system based on template matching, histogram equalization or log transform is applied to an input image for the intensity normalization and the image improvement. It is known that they are noneffective in improving an image with intensity distortion by illumination variation. In this paper, we propose an efficient image improvement method called as a bilateral symmetry average for images with intensity distortion by illumination variation. Experimental results show that our method delivers the detection performance better than previous methods and also remarkably reduces the number of face candidates.

• Information Display
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• v.4 no.2
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• pp.3-6
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• 2003

This paper describes a MacMic System developed for Flat Panel Display. The MacMic System usually is used for testing of Mother Glass of TFT and Color Filter. They are normally consisted of microscopy system, illumination system and panel stage system.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.396-406
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• 2006

This paper proposes an omni-directional image generation algorithm with parametric image compensation. The algorithm generates an omni-directional image by transforming each planar image to the spherical image on spherical coordinate. Parametric image compensation method is presented in order to compensate vignetting and illumination distortions caused by properties of a camera system and lighting condition. The proposed algorithm can generates realistic and seamless omni-directional video and synthesize any point of view from the stitched omni-directional image on the spherical image. Experimental results show that the proposed omni-directional system with vignetting and illumination compensation is approximately $1{\sim}4dB$ better than that which does not consider the said effects.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1287-1292
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• 2005

This paper presents an effective pattern classification model by designing an artificial neural network based pattern classifiers for face recognition. First, a RGB image inputted from a frame grabber is converted into a HSV image which is similar to the human beings' vision system. Then, the coarse facial region is extracted using the hue(H) and saturation(S) components except intensity(V) component which is sensitive to the environmental illumination. Next, the fine facial region extraction process is performed by matching with the edge and gray based templates. To make a light-invariant and qualified facial image, histogram equalization and intensity compensation processing using illumination plane are performed. The finally extracted and enhanced facial images are used for training the pattern classification models. The proposed H-ART2 model which has the hierarchical ART2 layers and F-LVQ model which is optimized by fuzzy membership make it possible to classify facial patterns by optimizing relations of clusters and searching clustered reference patterns effectively. Experimental results show that the proposed face recognition system is as good as the SVM model which is famous for face recognition field in recognition rate and even better in classification speed. Moreover high recognition rate could be acquired by combining the proposed neural classification models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1104-1113
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• 2015

In this paper, we propose Two-Dimensional Robust Face Recognition System Realized with the Aid of Facial Symmetry with Illumination Variation. Preprocessing process is carried out to obtain mirror image which means new image rearranged by using difference between light and shade of right and left face based on a vertical axis of original face image. After image preprocessing, high dimensional image data is transformed to low-dimensional feature data through 2-directional and 2-dimensional Principal Component Analysis (2D)2PCA, which is one of dimensional reduction techniques. Polynomial-based Radial Basis Function Neural Network pattern classifier is used for face recognition. While FCM clustering is applied in the hidden layer, connection weights are defined as a linear polynomial function. In addition, the coefficients of linear function are learned through Weighted Least Square Estimation(WLSE). The Structural as well as parametric factors of the proposed classifier are optimized by using Particle Swarm Optimization(PSO). In the experiment, Yale B data is employed in order to confirm the advantage of the proposed methodology designed in the diverse illumination variation

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Electrical & Electronic Materials
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• v.9 no.10
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• pp.1027-1032
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• 1996

The auto-illumination controller for office, residence, and so on was studied. The system consists of parts of a power supply, a signal oscillator, a lamp controller and two kinds of sensor. The lamp controller has two thyristors triggered by the IR sensor(SCRI) and CdS sensor(SCR2) respectively, When the illuminance around this system is higher than operating value of its sensor, lamp is turned off automatically. Otherwise, the light of lamp gets dim by CdS sensor. In case IR sensor senses the body heat of people around itself, the illuminance of the lamp gets maximum. The illuminance of the lamp can be changed dimmly by control of the variable resistor (RV) connected with SCR2 in series. The turning - on time of the lamp can be also controlled using a variable resistor(Rt) connected with a signal oscillator in parallel. Changing resistance Rt changes the time constant(.tau.), which triggers the gate of SCR2. Though people left the surrounding of lamp, the lamp keeps light for a while.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.38-43
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• 2011

We have developed a simple model of a bright-room contrast ratio (BRCR) measurement system for plasma display panels (PDPs) adopting a contrast enhancement film (CEF) by using an illumination design tool. Only four model parameters were used, namely, total ambient illumination power delivered by fluorescent lamps, a panel scattering rate, illuminance of PDP white patterns, and the absorption coefficient of a color adjusting film. These parameters were determined by simple optical measurements and matching simulations. The proposed model was employed to predict the BRCR values of four different CEF samples, and the simulated ones were found to be in agreement with measured ones within about 10% relative-error.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.9-16
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• 2005

This paper focuses on the study of the face authentication system and the robustness of fact authentication methods under illumination changes. Four different face authentication methods are tried. These methods are as fellows; PCA(Principal Component Analysis), GMM(Gaussian Mixture Modeis), 1D HMM(1 Dimensional Hidden Markov Models), Pseudo 2D HMM(Pseudo 2 Dimensional Hidden Markov Models). Experiment results involving an artificial illumination change to fate images are compared with each other. Face feature vector extraction based on the 2D DCT(2 Dimensional Discrete Cosine Transform) if used. Experiments to evaluate the above four different fate authentication methods are carried out on the ORL(Olivetti Research Laboratory) face database. Experiment results show the EER(Equal Error Rate) performance degrade in ail occasions for the varying ${\delta}$. For the non illumination changes, Pseudo 2D HMM is $2.54{\%}$,1D HMM is $3.18{\%}$, PCA is $11.7{\%}$, GMM is $13.38{\%}$. The 1D HMM have the bettor performance than PCA where there is no illumination changes. But the 1D HMM have worse performance than PCA where there is large illumination changes(${\delta}{\geq}40$). For the Pseudo 2D HMM, The best EER performance is observed regardless of the illumination changes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.351-356
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• 2011

In this paper, we design a pet location tracking and remote monitoring system that uses ultrasonic, temperature, humidity and illumination sensors to study behavioral patterns and habits. Using ultrasonic waves to calculate distances, a WSN(Wireless Sensor Network) was constructed to transmit data at pet's location, such as temperature, humidity and illumination, to a sink mote. Data received by the system are stored in the database in real time to trace pet's location. Interference among transmitting motes was eliminated by sequentially transmitting RF beacons using sink mote's beacon as the reference signal. Experiments were performed with the laboratory prototype of a pet animal monitoring system implemented for this study. The system analyzes locations of a pet and displays movement patterns, areas of movement, temperature, humidity and illumination using a GUI (graphical user interface).