• Proceedings of the KSRS Conference
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• v.1
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• pp.491-494
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• 2006

The west coast of Northern Borneo is strongly influenced by Asian monsoon. Present research using the satellite ocean color (OC) remote sensing has identified some interesting oceanographic phenomena in this area that could be related to the harmful algal blooms (HAB). Occurrence of seasonal upwelling event was noticed off the northern tip of Borneo Island that could be related to the northeast monsoon wind. Harmful algal blooms by Pyrodinium bahamense var. compressum occurred since 1976. Subsequently, during December 2003, there was a report of new HAB by Cochlodinium polykrikoides in Northern Borneo. Analysis of OC images revealed that the Cochlodinium bloom had very high chlorophyll a signal and strong absorption characteristics. Results showed that the Baram River plume and upwelling at Northern Borneo were the source of nutrient for the Cochlodinium bloom in the offshore region. Ocean color images of 2004 showed that the bloom from Northern Borneo had crossed the Balabac Straits, reaching Palawan Island in Philippine. Due to the possibility of transboundary HAB problem, we propose a regional HAB monitoring network for an effective HAB management.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.50-57
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• 2005

We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.281-284
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• 2010

In this paper, we present Hand-gesture recognition for actual computing into color images from camera. Color images are binarization and labeling by using the YCbCr Color model. Respectively label area seeks the center point of the hand from to search Maximum Inscribed Circle which applies Voronoi-Diagram. This time, searched maximum circle and will analyze the elliptic ingredient which is contiguous so a hand territory will be able to extract. we present the presentation contral system using elliptic element and Maximum Inscribed Circle. This algorithm is to recognize the various environmental problems in the hand gesture recognition in the background objects with similar colors has the advantage that can be effectively eliminated.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.6
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• pp.662-670
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• 2005

With highly oxygenated fuels the smoke emissions decreased sharply and linearly with increases in the fuel oxygen content and entirely disappeared at an oxygen content of $38wt-\%$ even at stoichiometric mixture conditions The NOx also decreased monotonically with increases in oxygen content. and thermal efficiency slightly improved because of a reduction in cooling loss and improvement in the degree of constant volume combustion. The mechanisms of the significant reductions in emissions and improvement in engine performance were analyzed with a bottom view type DI diesel engine. Together with direct flame images, flame images were taken through an optical fetter passing only two wavelengths for use in 2-D two-color analysis. The results showed that luminous flame decreased significantly with increases in oxygen content and was not detected for neat dimethoxy methane(DMM). The decrease in flame luminosity with highly oxygenated fuels corresponds with decreases in soot and cooling losses, including those due to heat radiation. The 2-D two-color flame analysis indicated that the high temperature flame and high KL factor areas apparently decreased with increasing fuel oxygen content. These results correspond strongly with decreases in NOx. smoke. and cooling loss with increases in oxygen content.

• Journal of the Korean Society of Visualization
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• v.15 no.1
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• pp.53-63
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• 2017

Sonic and supersonic jets include many complicated flow physics associated with shock waves, shear layers, vortices as well as strong interactions among them, and have a variety of engineering applications. Much has been learned from the previous researches on the sonic and supersonic jets but quantitative assessment of these jets is still uneasy due to the high velocity of flow, compressibility effects, and sometimes flow unsteadiness. In the present study, the sonic jets issuing from a convergent nozzle were measured by PIV and Schlieren optical techniques. Particle Image Velocimetry (PIV) with Olive oil particles of $1{\mu}m$ was employed to obtain the velocity field of the jets, and the black-white and color Schlieren images were obtained using Xe ramp. A color filter of Blue-Green-Red has been designed for the color Schlieren and obtained from an Ink jet printer. In experiments, two types of sonic nozzles were used at different operating pressure ratios(NPR). The obtained images clearly showed the major features of the jets such as Mach disk, barrel shock waves, jet boundaries, etc.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.583-586
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• 1999

In this paper, the wavelet transform is performed in the input 256$\times$256 color image and decomposes a image into low-pass and high-pass components. Since the high-pass band contains the components of three directions, edges are detected by combining three parts. After finding the position of face using the histogram of the edge component, a face region in low-pass band is cut off. Since RGB color image is sensitively affected by luminances, the image of low pass component is normalized, and a facial region is detected using face color informations. As the wavelet transform decomposes the detected face region into three layer, the dimension of input image is reduced. In this paper, we use the 3000 images of 10 persons, and KL transform is applied in order to classify face vectors effectively. FCM(Fuzzy C-Means) algorithm classifies face vectors with similar features into the same cluster. In this case, the number of cluster is equal to that of person, and the mean vector of each cluster is used as a codebook. We verify the system performance of the proposed algorithm by the experiments. The recognition rates of learning images and testing image is computed using correlation coefficient and Euclidean distance.

• Journal of Sensor Science and Technology
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• v.21 no.3
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• pp.211-216
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• 2012

Fires are the most common disaster and early fire detection is of great importance to minimize the consequent damage. Simple sensors including smoke detectors are widely used for the purpose but they are able to sense fires only at close proximity. Recently, due to the rapid advances of relevant technologies, vision-based fire sensing has attracted growing attention. In this paper, a novel visual sensing technique to automatically detect fire is presented. The proposed technique consists of multiple steps of image processing: pixel-level, block-level, and frame level. At the first step, fire flame pixel candidates are selected based on their color values in YIQ space from the image of a camera which is installed as a vision sensor at a fire scene. At the second step, the dynamic parts of flames are extracted by comparing two consecutive images. These parts are then represented in regularly divided image blocks to reduce pixel-level detection error and simplify following processing. Finally, the temporal change of the detected blocks is analyzed to confirm the spread of fire. The proposed technique was tested using real fire images and it worked quite reliably.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.913-918
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• 2007

Human motion analysis is an important research subject in human-robot interaction (HRI). However, before analyzing the human motion, silhouette of human body should be extracted from sequential images obtained by CCD camera. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. In this paper, we discuss the hybrid silhouette extraction method for detecting and tracking the human motion. The proposed method is to combine and optimize the temporal and spatial gradient information. Also, we propose some compensation methods so as not to miss silhouette information due to poor images. Finally, we have shown the effectiveness and feasibility of the proposed method through some experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.286-294
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• 2011

In most digital cameras, images are obtained by a sensor overlaid by the color filter array (CFA) such as Bayer, demanding a demosaicking procedure to rebuild the full resolution color images. However, due to the nature of sensor, it is necessary to consider denoising step to remove the noise. In this paper, we analyze demosaicking and denoising jointly and show that the proposed method can solve the denoising issue by simple manner, well suppress different level of noises. The proposed algorithm yields comparable performances measured by several image quality assessment (CPSNR, SCIELAB, and FSIM), while the computational cost is low.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.85-91
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• 2017

Lenses have different refractive indices for different wavelengths of light. This is why different wavelengths of rays are focused at different positions in the focal plane. Images are blurred and noticeable colored edges appear around the objects, which is known as chromatic aberration (CA). In this paper, an algorithm for removing CA artifacts in color images is proposed. Based on the fact that the gradients of color channels are highly correlated, the differences of the gradients of the channels in edges are minimized. The cost function is designed by using the gradients of the channels. Experimental results show the good performance of the proposed algorithm in removing the CA artifacts.