• Proceedings of the KAIS Fall Conference
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• 2006.11a
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• pp.220-224
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• 2006

The text to be included in the natural images has many important information in the natural image. Therefore, if we can extract the text in natural images, It can be applied to many important applications. In this paper, we propose a text region extraction method using pattern histogram of character-edge map. We extract the edges with the Canny edge detector and creates 16 kind of edge map from an extracted edges. And then we make a character-edge map of 8 kinds that have a character feature with a combination of an edge map. We extract text region using 8 kinds of character-edge map and 16 kind of edge map. Verification of text candidate region uses analysis of a character-edge map pattern histogram and structural feature of text region. The method to propose experimented with various kind of the natural images. The proposed approach extracted text region from a natural images to have been composed of a complex background, various letters, various text colors effectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.615-622
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• 2007

In general, Harris detector is commonly used for finding salient points in watermarking systems using feature points. Harris detector is a kind of combined comer and edge detector which is based on neighboring image data distribution, therefore it has some limitation to find accurate salient points after watermark embedding or any kinds of digital attacks. In this paper, we have used cross reference points which use not data distribution but geometrical structure of a normalized image in order to avoid pointing error caused by the distortion of image data. After normalization, we find cross reference points and take inverse normalization of these points. Next, we construct a group of triangles using tessellation with inversely normalized cross reference points. The watermarks are affine transformed and transformed-watermarks are embedded into not normalized image but original one. Only locations of watermarks are determined on the normalized image. Therefore, we can reduce data loss of watermark which is caused by inverse normalization. As a result, we can detect watermarks with high correlation after several digital attacks.

• Transactions on Semiconductor Engineering
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• v.2 no.1
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• pp.17-20
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• 2024

This paper presents a novel lightweight object detection model tailored for low-powered edge devices, addressing the limitations of traditional resource-intensive computer vision models. Our proposed detector, inspired by the Single Shot Detector (SSD), employs a compact yet robust network design. Crucially, it integrates an 'enhancer block' that significantly boosts its efficiency in detecting smaller objects. The model comprises two primary components: the Light_Block for efficient feature extraction using Depth-wise and Pointwise Convolution layers, and the Enhancer_Block for enhanced detection of tiny objects. Trained from scratch on the Udacity Annotated Dataset with image dimensions of 300x480, our model eschews the need for pre-trained classification weights. Weighing only 5.5MB with approximately 0.43M parameters, our detector achieved a mean average precision (mAP) of 27.7% and processed at 140 FPS, outperforming conventional models in both precision and efficiency. This research underscores the potential of lightweight designs in advancing object detection for edge devices without compromising accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.422-433
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• 2001

In this paper, we propose a flew edge detection method based on water flow model, in which gradient image surface is considered as a 3-dimensional (3-D) geographical feature. The edges of the objects in the background can be detected by the large gradient magnitude areas and to make the edges immersed it is required to invert the gradient image. The proposed edge detector uses a water flow model based enhancement and locally adaptive thresholding technique applied to the inverted gradient image resulting in better noise performance. Computer simulations with a few synthetic and real images show that the Proposed method can extract edge contour effectively.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.359-367
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• 2011

A suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. The research on pan-sharpening algorithm in improving the accuracy of image classification has been reported. For a classification, preserving the spectral information is important. Other applications such as road detection depend on a sharp and detailed display of the scene. Various criteria applied to scenes with different characteristics should be used to compare the pan-sharpening methods. The pan-sharpening methods in our research comprise rather common techniques like Brovey, IHS(Intensity Hue Saturation) transform, and PCA(Principal Component Analysis), and more complex approaches, including wavelet transformation. The extraction of matching pairs was performed through SIFT descriptor and Canny edge detector. The experiments showed that pan-sharpening techniques for spatial enhancement were effective for extracting point and linear features. As a result of the validation it clearly emphasized that a suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. In future it is necessary to design hybrid pan-sharpening for the updating of features and land-use class of a map.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1887-1890
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm using the stereo image. Given a pair of stereo image, we automatically extract several important facial feature points using the disparity map, the gabor filter and the canny edge detector. To detect the facial feature region , we propose a region dividing method using the disparity map. On the indoor head & shoulder stereo image, a face region has a larger disparity than a background. So we separate a face region from a background by a divergence of disparity. To estimate 3D head pose, we propose a 2D-3D Error Compensated-SVD (EC-SVD) algorithm. We estimate the 3D coordinates of the facial features using the correspondence of a stereo image. We can estimate the head pose of an input image using Error Compensated-SVD (EC-SVD) method. Experimental results show that the proposed method is capable of estimating pose accurately.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.75-83
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• 2008

We propose a welfare interface using multiple fecial features tracking, which can efficiently implement various mouse operations. The proposed system consist of five modules: face detection, eye detection, mouth detection, facial feature tracking, and mouse control. The facial region is first obtained using skin-color model and connected-component analysis(CCs). Thereafter the eye regions are localized using neutral network(NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then mouth region is localized using edge detector. Once eye and mouth regions are localized they are continuously and correctly tracking by mean-shift algorithm and template matching, respectively. Based on the tracking results, mouse operations such as movement or click are implemented. To assess the validity of the proposed system, it was applied to the interface system for web browser and was tested on a group of 25 users. The results show that our system have the accuracy of 99% and process more than 21 frame/sec on PC for the $320{\times}240$ size input image, as such it can supply a user-friendly and convenient access to a computer in real-time operation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.872-877
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• 2012

We proposes the method to detect the Hangul character region from natural image using topological structural feature of Hangul grapheme. First, we transform a natural image to a gray-scale image. Second, feature extraction performed with edge and connected component based method, Edge-based method use a Canny-edge detector and connected component based method applied the local range filtering. Next, if features are not corresponding to the heuristic rule of Hangul character, extracted features filtered out and select candidates of character region. Next, candidates of Hangul character region are merged into one Hangul character using Hangul character merging algorithm. Finally, we detect the final character region by Hangul character class decision algorithm. Experimental result, proposed method could detect a character region effectively in images that contains a complex background and various environments. As a result of the performance evaluation, A proposed method showed advanced results about detection of Hangul character region from mobile image.

• Proceedings of the Korea Crystallographic Association Conference
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• 2002.11a
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• pp.5-6
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• 2002

The new spectrometer for X-ray Induced Electron Emission Spectroscopy (XIEES) .has been recently developed in KRISS in collaboration with PTI (Russia). The spectrometer allows to perform research using the XAFS, SXAFS, XANES techniques (D.C.Koningsberger and R.Prins, 1988) as well as the number of techniques from XIEES field(L.A.Bakaleinikov et all, 1992). The experiments may be carried out with registration of transmitted through the sample x-rays (to investigate bulk samples) or/and total electron yield (TEY) from the sample surface that gives the high (down to several atomic mono-layers in soft x-ray region) near surface sensitivity. The combination of these methods together give the possibility to obtain a quantitative information on elemental composition, chemical state, atomic structure for powder samples and solids, including non-crystalline materials (the long range order is not required). The optical design of spectrometer is made according to Johannesson true focusing schematics and presented on the Fig.1. Five stepping motors are used to maintain the focusing condition during the photon energy scan (crystal angle, crystal position along rail, sample goniometer rail angle, sample goniometer position along rail and sample goniometer angle relatively of rail). All movements can be done independently and simultaneously that speeds up the setting of photon energy and allows the using of crystals with different Rowland radil. At present six curved crystals with different d-values and one flat synthetic multilayer are installed on revolver-type monochromator. This arrangement allows the wide range of x-rays from 100 eV up to 25 keV to be obtained. Another 4 stepping motors set exit slit width, sample angle, channeltron position and x-ray detector position. The differential pumping allows to unite vacuum chambers of spectrometer and x-ray generator avoiding the absorption of soft x-rays on Be foil of a window and in atmosphere. Another feature of vacuum system is separation of walls of vacuum chamber (which are deformed by the atmospheric pressure) from optical elements of spectrometer. This warrantees that the optical elements are precisely positioned. The detecting system of the spectrometer consists of two proportional counters, one scintillating detector and one channeltron detector. First proportional counter can be used as I/sub 0/-detector in transmission mode or by measuring the fluorescence from exit slit edge. The last installation can be used to measure the reference data (that is necessary in XANES measurements), in this case the reference sample is installed on slit knife edge. The second proportional counter measures the intensity of x-rays transmitted through the sample. The scintillating detector is used in the same way but on the air for the hard x-rays and for alignment purposes. Total electron yield from the sample is measured by channeltron. The spectrometer is fully controlled by special software that gives the high flexibility and reliability in carrying out of the experiments. Fig.2 and fig.3 present the typical XAFS spectra measured with spectrometer.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.930-935
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• 2014

A Gabor filter is a linear filter used for edge detectionas frequency and orientation representations of Gabor filters are similar to those of the human visual system. In this thesis, we propose a pedestrian detection algorithm using a Gabor filter bank. In order to extract the features of the pedestrian, we use various image processing algorithms and data structure algorithms. First, color image segmentation is performed to consider the information of the RGB color space. Second, histogram equalization is performed to enhance the brightness of the input images. Third, convolution is performed between a Gabor filter bank and the enhanced images. Fourth, statistical values are calculated by using the integral image (summed area table) method. The calculated statistical values are used for the feature matrix of the pedestrian area. To evaluate the proposed algorithm, the INRIA pedestrian database and SVM (Support Vector Machine) are used, and we compare the proposed algorithm and the HOG (Histogram of Oriented Gradient) pedestrian detector, presentlyreferred to as the methodology of pedestrian detection algorithm. The experimental results show that the proposed algorithm is more accurate compared to the HOG pedestrian detector.