• Journal of Electrical Engineering and Technology
• /
• v.10 no.4
• /
• pp.1822-1829
• /
• 2015

In this study, artificial neural networks were used to determine the intensity of brightness in interior spaces. The illumination elements to illuminate indoor spaces were considered, not individually, but as a system. So, during the planned maintenance periods of an illumination system, after its design and installation, simple brightness level measurements must be taken. For a three-dimensional evaluation of the brightness level in indoor spaces in a speedy and accurate manner, the obtained brightness level measurement results and artificial neural network model were used. Upon estimation of the most suitable brightness level for indoor spaces by using the artificial neutral network model, the energy demands required by the illumination elements decreased. Consequently, in this study, with estimations of brightness levels, the extent to which the artificial neutral networks become successful was observed and more correct results have been obtained in terms of both economy and usage.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.3
• /
• pp.1000-1012
• /
• 2000

There are many factors for face recognition. Two of those are orientation and brightness of illumination. In early studies of face recognition, with fixing these factors to good conditions th goal of research was focused on improving recognition rate itself. But they are very important factors to be solved for implementing face recognition system. In this paper, two methods wer proposed to minimize the influence of illumination. One is the local difference filter to reduce the influence fo variation of illumination. The other is weight function considering the horizontal difference of intensity. Applying tow proposed methods, the resultant recognition rate revealed 86.5% for 275 test images.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.456-458
• /
• 2004

Recent medical robot systems perform surgery operations, by following the preplanned trajectory and surgical procedures. Depending on the complexity of surgery operations, they are operated in manual, semi-automatic or full automatic mode. To improve the performance of those medical robot systems, development of the simulator and more advanced auto-illumination system, in which intensity of light, direction and focal point can be controlled automatically according to the varied environments during surgical operations. are required. Therefore, in this paper, the simulator for SPINEBOT system which is a computer-intergrated robotic surgery system are developed. And further, an auto-illumination system which will be integrated to the SPINEBOT system is investigated and its preliminary design is described.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.2
• /
• pp.301-312
• /
• 1996

A new approach is presented for recovering the 3-D shape from shading image. Photometric Stereo Method (PSM) is generally based on the direct illumination. In this paper, the reflectance function is derived by introduceing the indirect diffuse illumination in PSM and then applied to hybrid reflectance model which consists fo two components; the Lambertian reflectance and the speclar reflectance. Under the hybrid reflectance model and the indirect diffuse illumination circumstances, the 3-D shape of object can be recovered from the suface normal vector extracted from the surface roughness, the surface reflectance ratio, and the intensity value of a pixel. This method is rapid because of using the reference table and simplifies the restriction condition about the reflectance function existing in prior studies. The recovery efficiency in our method is better than that in prior studies. Also, this method is applied to various types of surfaces by defining general reflectance function.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.15-17
• /
• 2006

This paper presents a new global intensity compensation method for extracting moving object in a visual surveillance system by compensating time variant intensity changes of background region. The method that compensates a little changes of intensity due to time variant illumination change and automatic gain control of camera is called global intensity compensation. The proposed method expresses global intensity change with a mapping table to describe complex form of intensity change while the previous method models this global intensity change with a simple function as a straight line. The proposed method builds the mapping table by calculating the cross histogram between two images and then by selecting an initial point for generating the mapping table by using Hough transform applied to the cross histogram image. Then starting from the initial point, the mapping table is generated according to the proposed algorithm based on the assumption that reflects the characteristic of global intensity change. Experimental results show that the proposed method makes the compensation error much smaller than the previous GIC method

• Current Optics and Photonics
• /
• v.7 no.6
• /
• pp.755-760
• /
• 2023

In this paper, an illumination optical system that can mitigate the saturation phenomenon in the center of an image (caused by the typical flexible-endoscope illumination system using LEDs with Lambertian light distribution) is designed. When an LED with Lambertian light distribution is used as a light source, the amount of light in the center of the endoscopic illumination system is relatively high, compared to the periphery, causing saturation in the image. Since this phenomenon causes difficulty in detecting the patient's lesion, it is necessary to find a lighting-system design that can alleviate the saturation phenomenon. Therefore, in this paper a lighting system with bat-wing light distribution, which can lower the intensity at the center and secure the maximum amount of light at the maximum light distribution angle, is designed. In addition, to check the performance of the designed lighting system, a simulation of illumination and luminance is conducted for a system using a common aspherical lens with otherwise the same components. As a result, it is confirmed that the lighting system designed in this paper effectively reduces the luminance value at the center and secures more luminance values at the periphery than the familiar lighting system.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.15 no.2
• /
• pp.107-114
• /
• 2007

We investigated mating conditions of photoperiod, illumination and temperature during mating periods, care temperature of queen before mating, mating period and number of queen per mating cage to improve mating rate of Bombus ignitus. Among photoperiodic regimes of 12L, 14L and 16L during mating periods, queen mated at 14L showed better results than at 12L and 16L in egg-laying characteristics and colony development. In case of illumination during mating periods, intensity of 1000 lux was more effective than at intensity of 100 lux and 2000 lux in mating B. ignitus queen. Mating temperature and care temperature of queen before mating favorable for B. ignitus queen were $22-25^{\circ}C$ and $19^{\circ}C$, respectively. The period need to mating B. ignitus queen was 3 days, and the number of queen suitable per mating cage of $55{\times}45{\time}65\;cm$ was 30.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.3
• /
• pp.265-272
• /
• 2009

In this paper, a simple optical method that uses an infrared(IR) cut filter is proposed to minimize variation of eye image by external infrared(IR) sources in a video based head mounted eye tracking system that is used in the field of sports. For this, the IR cut filter is attached to a head mount of the eye tracking system, and the camera with an IR LED is located between the IR cut filter and eye. In this structure, external IR is blocked by the IR cut filter, and the IR intensity on the eye can be controlled by the IR LED. Therefore, the illumination condition of the camera to capture the eye can be stable without being affected by external IR illuminations. To verify the proposed idea, variation of the eye image and intensity of the IR with/without the IR cut filter is measured under various illumination conditions. The measured data show that the IR cut filter method can block external IR effectively, and complex pupil detection algorithms can be replaced by a simple binarized method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.6
• /
• pp.2289-2301
• /
• 2015

Mobile devices are becoming powerful enough to realize augmented reality (AR) application. This paper introduces two AR methods to estimate an environmental illumination distribution of a scene. In the first method, we extract the lighting direction and intensity from input images captured with a front-side camera of a mobile device, using its orientation sensor. The second method extracts shadow regions cast by three dimensional (3D) AR marker of known shape and size. Because previous methods examine per pixel shadow intensity, their performances are much affected by the number of sampling points, positions, and threshold values. By using a simple binary operation between the previously clustered shadow regions and the threshold real shadow regions, we can compute efficiently their relative area proportions according to threshold values. This area-based method can overcome point sampling problem and threshold value selection. Experiment results demonstrate that the proposed methods generate natural image with multiple smooth shadows in real-time.

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