• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.5
• /
• pp.225-232
• /
• 2009

In this paper, a new face detection method based on pupil color distribution maps with the frequency under the illumination variance is proposed. Face-like regions are first extracted by applying skin color distribution maps to a color image and then, they are reduced by using the standard deviation of chrominance components. In order to search for eye candidates effectively, the proposed method extracts eye-like regions from face-like regions by using pupil color distribution maps. Furthermore, the proposed method is able to detect eyes very well by segmenting the eye-like regions, based on a lighting compensation technique and a segmentation algorithm even though face regions are changed into dark-tone due to varying illumination conditions. Eye candidates are then detected by means of template matching method. Finally, face regions are detected by using the evaluation values of two eye candidates and a mouth. Experimental results show that the proposed method can achieve a high performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.227-232
• /
• 2003

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. eased on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.6 s.312
• /
• pp.46-56
• /
• 2006

In this paper, we propose an improved reproduction algorithm for a realistic image of the real scene based on the optical characteristics of the light sources and the materials at the lighting environment. This paper is continuation of the previous study to improve the modeling method of the light sources and the materials and apply this to the real rear lamp of automobile. The backward ray tracing method is first used to trace the light ray from a light source, and also considers the physical characteristics of object surfaces and geometric properties of light radiation to estimate accurately the light energy incoming toward to human eyes. For experiments and verification of the proposed method, the simulation results are compared with the measured light stimuli. Accordingly, the simulation results show that the proposed algorithm can estimate light energy well and reproduce the visually similar image with a scene incident on a sight of viewer.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.1
• /
• pp.57-64
• /
• 2013

In this paper, we propose the classification method of medicine bottle images using the features with color and size information. It is difficult to classify with size feature only, because there are many similar sizes of bottles. Therefore, we suggest a classification method based on color information, which robust to illumination variations. First, we extract MBR(Minimum Boundary Rectangle) of medicine bottle area using Binary Threshold of Red, Green, and Blue in image and classify images with size. Then, hue information and RGB color average rate are used to classify image, which features are robust to lighting variations. Finally, using SURF(Speed Up Robust Features) algorithm, corresponding image can be found from candidates with previous extracted features. The proposed method makes to reduce execution time and minimize the error rate and is confirmed to be reliable and efficient from experiment.

• Journal of the Korea Computer Graphics Society
• /
• v.21 no.3
• /
• pp.36-45
• /
• 2015

It is important subject of research in engineering and natural science field that creating continuing high-definition image from very large volume data. The necessity of software that helps analyze useful information in data has improved by effectively showing visual image information of high resolution data with visualization technique. In this paper, we designed multi-platform visualization system based on client-server to analyze and express earth environment data effectively constructed with observation and prediction. The visualization server comprised of cluster transfers data to clients through parallel/distributed computing, and the client is developed to be operated in various platform and visualize data. In addition, we aim user-friendly program through multi-touch, sensor and have made realistic simulation image with image-based lighting technique.

• Journal of Korea Multimedia Society
• /
• v.14 no.5
• /
• pp.607-613
• /
• 2011

In this paper, we propose a hand image segmentation method using the dynamic threshold values on input images with various lighting and background attributes. First, a moving hand silhouette is extracted using the camera input difference images, Next, based on the R,G,B histogram analysis of the extracted hand silhouette area, the threshold interval for each R, G, and B is calculated on run-time. Finally, the hand area is segmented using the thresholding and then a morphology operation, a connected component analysis and a flood-fill operation are performed for the noise removal. Experimental results on various input images showed that our hand segmentation method provides high level of accuracy and relatively fast stable results without the need of the fixed threshold values. Proposed methods can be used in the user interface of mixed reality applications.

• Smart Media Journal
• /
• v.13 no.11
• /
• pp.59-70
• /
• 2024

Detecting objects in underwater environments is challenging due to factors such as object overlap, noise, and lighting variations. In particular, labeling underwater organisms like Paralichthys olivaceus requires significant time and effort when done manually. To address these challenges, this paper proposes a method to automate the labeling of Paralichthys olivaceus using image processing techniques and to increase the size of the dataset for training. The proposed method applies morphological operations and contour detection to remove noise and accurately extract object boundaries. Additionally, the Y0L0v8 model is used to analyze performance variations based on dataset size and training methods. The results demonstrate that expanding the dataset through automated image preprocessing improves object detection performance, even in cases of object overlap, and proves to be more time-efficient compared to manual labeling.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.8
• /
• pp.77-86
• /
• 2014

Mobile devices are generally using app images which are artificially designed. Accordingly, this paper presents adjusting device brightness based on app image categorization for enhancing the visibility under various light condition. First, the proposed method performed two prior subjective tests under various lighting conditions for selecting features of app images concerning visibility and for selecting satisfactory range of device brightness for each app image. Then, the relationship between selected features of app image and satisfactory range of device brightness is analyzed. Next, app images are categorized by using two features of average brightness of app image and distribution ratio of advanced colors that are related to satisfaction range of device brightness. Then, optimal device brightness for each category is selected by having the maximum frequency of satisfaction device brightness. Experimental results show that the categorized app images with optimal device brightness have high satisfaction ratio under various light conditions.

• Journal of Digital Convergence
• /
• v.17 no.4
• /
• pp.255-260
• /
• 2019

This study is about an efficient synthesis of $360^{\circ}$ video and 3D graphics. First, the video image filmed by a binocular integral type $360^{\circ}$ camera was stitched, and location values of the camera and objects were extracted. And the data of extracted location values were moved to the 3D program to create 3D objects, and the methods for natural compositing was researched. As a result, as the method for natural compositing of $360^{\circ}$ video image and 3D graphics, rendering factors and rendering method were derived. First, as for rendering factors, there were 3D objects' location and quality of material, lighting and shadow. Second, as for rendering method, actual video based rendering method's necessity was found. Providing the method for natural compositing of $360^{\circ}$ video image and 3D graphics through this study process and results is expected to be helpful for research and production of $360^{\circ}$ video image and VR video contents.