• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.688-693
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• 2010

Vision based object recognition in mobile robots has many issues for image analysis problems with neighboring elements in dynamic environments. SURF(Speeded Up Robust Features) is the local feature extraction method of the image and its performance is constant even if disturbances, such as lighting, scale change and rotation, exist. However, it has a difficulty of real-time processing caused by representation of high dimensional vectors. To solve th problem, execution of SURF in GPU(Graphics Processing Unit) is proposed and implemented using CUDA of NVIDIA. Comparisons of recognition rates and processing time for SURF between CPU and GPU by variation of robot velocity and image sizes is experimented.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.206-210
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• 2011

Vision-based robot localization is challenging due to the vast amount of visual information available, requiring extensive storage and processing time. To deal with these challenges, we propose the use of features extracted from omni-directional panoramic images and present a method for localization of a mobile robot equipped with an omni-directional camera. The core of the proposed scheme may be summarized as follows : First, we utilize an omni-directional camera which can capture instantaneous $360^{\circ}$ panoramic images around a robot. Second, Nodes around the robot are extracted by the correlation coefficients of Circular Horizontal Line between the landmark and the current captured image. Third, the robot position is determined from the locations by the proposed correlation-based landmark image matching. To accelerate computations, we have assigned the node candidates using color information and the correlation values are calculated based on Fast Fourier Transforms. Experiments show that the proposed method is effective in global localization of mobile robots and robust to lighting variations.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.12
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• pp.31-41
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• 2019

Biophilic design gives human beings positive and valuable experiences in nature. The experience in nature in the architectural environment is mainly symbolic and metaphorical, and is based on visual sensations such as color, form, and image. Recently, modern people living in a modern and simple style indoor space have a desire to pursue visual stimuli for interest or pleasure. This desire can be satisfied through color, lighting, and finishing plan. Therefore, the purpose of this study is to propose a biophilic design color palette based on the empirical characteristics and properties of biophilic design. The methods used in this study are as follows. First, the biophilic design factors and natural landscape preference criteria are examined. Second, based on the review results, natural landscape images are selected and color information for each biophilic design element is extracted according to the vertical and horizontal directions. Third, color information is converted to NCS color code and palette range and hue range are derived through the analysis of ratio and average values. Finally, based on the analysis results, biophilic design color palette is proposed for each element. The results of this study might be useful as basic data in establishing biophilic design strategies and applying them to architecture and interior construction.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.395-403
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• 2016

Recently, Image processing has been used in many areas. In the image processing techniques that a lot of research is tracking of moving object in real time. There are a number of popular methods for tracking an object such as HOG(Histogram of Oriented Gradients) to track pedestrians, and Codebook to subtract background. However, object extraction has difficulty because that a moving object has dynamic background in the image, and occurs severe lighting changes. In this paper, we propose a method of object extraction using depth image and color image features based on ROI(Region of Interest). First of all, we look for the feature points using the color image after setting the ROI a range to find the location of object in depth image. And we are extracting an object by creating a new contour using the convex hull point of object and the feature points. Finally, we compare the proposed method with the existing methods to find out how accurate extracting the object is.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2355-2358
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• 2003

The purpose of this paper is to investigate two major feature extraction techniques based on generic modular face recognition system. Detailed algorithms are described for principal component analysis (PCA) and independent component analysis (ICA). PCA and ICA ate statistical techniques for feature extraction and their incorporation into a face recognition system requires numerous design decisions. We explicitly state the design decisions by introducing a modular-based face recognition system since some of these decision are not documented in the literature. We explored different implementations of each module, and evaluate the statistical feature extraction algorithms based on the FERET performance evaluation protocol (the de facto standard method for evaluating face recognition algorithms). In this paper, we perform two experiments. In the first experiment, we report performance results on the FERET database based on PCA. In the second experiment, we examine performance variations based on ICA feature extraction algorithm. The experimental results are reported using four different categories of image sets including front, lighting, and duplicate images.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.173.1-173
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• 2001

This paper proposes the methodology in image processing algorithm that estimates the pose of the pipe crawling robot. The pipe crawling robots are usually equipped with a lighting device and a camera on its head for monitoring and inspection purpose. The proposed methodology is using these devices without introducing the extra sensors and is based on the fact that the position and the intensity of the reflected light varies with the robot posture. The algorithm is divided into two parts, estimating the translation and rotation angle of the camera, followed by the actual pose estimation of the robot. To investigate the performance of the algorithm, the algorithm is applied to a sewage maintenance robot.

• Journal of Fashion Business
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• v.11 no.6
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• pp.115-124
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• 2007

The cross-section of the polyester filament yarn has been modified to have a variety of shape for aesthetic, added functions and sensitivities, and other purposes. Transparent polyester filament of trilobal cross-section has unique optical properties with high anisotropic reflectivity and transmissivity. The monofilament yarns may be utilized to impart to the fabrics lustrous appearance along with unique color change in case differently dyed yarns are woven together. The color changes of the fabric specimens according to the changes in observation and lighting conditions were analyzed using a CCD camera and an image analysis software. The changes of color/luster of the fabric specimens were measured and analyzed based on RGB, $L^*a^*b^*,\;L^*C^*h,$ and the color distribution within a three-dimensional color space.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.673-676
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• 2017

In this paper, we propose a day and night fog detection algorithm that is not affected by lighting conditions. First, we present the definitions and the extraction methods of fog features in daytime and nighttime environments, respectively. We then propose the fog detection algorithm using a neural network from the fog features. A set of experiments has been conducted with images taken at various environments, and the average recall of the proposed algorithm is 97.5%.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.168-174
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• 1993

A new digital image processing method for measuring of the flank wear of cutting tool is presented. The method is based on computer vision technology in which the tool is illuminated by two halogen lamps and the wear zone is visualized using a CCD camera. The image is converted into digital pixel and processed to detect the wearland width. As a conclusion, it has been proved that the average wearland area and mzximum peak values of the flank wear width can monitored effectively to a measuring resolution of 0.01mm.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.199-204
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• 2024

This study aims to explore the issue of character consistency in AI-generated artwork. First, the concept of character consistency is explained, including the consistency of appearance, actions, and lighting, and its importance in continuous creation and storytelling is analyzed. Next, the study examines current mainstream AI drawing tools such as MidJourney and Stable Diffusion-based WebUI and ComfyUI, evaluating their strengths and limitations in maintaining character consistency. Finally, methods to improve AI drawing technology were proposed to enhance character consistency, aiming to achieve a higher level of consistency in AI art creation.