• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.719-721
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• 2013

A thinning stage of fingerprint algorithm occupies 39% cycle of microprocessor system for identification processing of image from fingerprint sensor. Hardware block processing is more effective than software one in speed and power consumption, because a thinning algorithm is iteration of simple instructions without a transcendental function. This paper describes an effective hardware scheme for thinning stage processing using Verilog-HDL in $64{\times}64$ Pixel Array. The hardware scheme is designed and simulated in RTL. The logic is also synthesized by XST in FPGA environment and tested. Experimental results show the performance of the proposed scheme and possibility of application for a soft microprocessor and thinning processor embedded fingerprint SoC.

• Proceedings of the Optical Society of Korea Conference
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• 2006.02a
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• pp.359-360
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• 2006

Functional photoacoustic tomography is a new non-invasive imaging modality, and it is emerging as a very practical method for imaging biological tissue structures by means of laser-induced ultrasound. Structures with high optical absorption, such as blood vessels, can be imaged with the spatial resolution of ultrasound, which is not limited by the strong light scattering in biological tissues. By varying wavelengths of the laser light and acquiring photoacoustic images, optical absorption spectrum of each image pixel is found. Since the biochemical constituents of tissues determine the spectrum, useful functional information like oxygen saturation ($SO_2$) and total haemoglobin concentration (HbT) can be extracted. In this study, as a proof-of-principle experiment, hypoxic brain tumor vasculature and traumatic brain injury (TBI) of small animal brain are imaged with functional photoacoustic tomography. High resolution brain vasculature images of oxygen saturation and total hemoglobin concentration are provided to visualize hypoxic tumor vasculature, and hemorrhage on the cortex surface by the TBI.

• International Journal of Contents
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• v.11 no.3
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• pp.47-53
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• 2015

Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.79-87
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• 2002

This paper proposes an approach of automatically identifying the center of fiducial marks using radiometric and geometric characteristics of those marks existing on aerial photographs. Candidate region surrounding a mark, based on radiometric strategy, is determined by producing a bi-level image and by applying morphological operations. Based on geometric strategy, the central location of a mark is determined by applying ${\bigtriangledown}^G$ filtering and symmetry-enhancement filtering, and by finding peak location of symmetry. Evaluation with respect to 66 cases of sub-images containing a fiducial mark showed that the central location of the mark is determined up to around one pixel difference whit it is compared to a manual inspection.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.229-233
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• 2004

원격탐사 자료를 이용하여 조간대 표층퇴적상의 분류가 가능하다면 현장조사와 상호 보완적으로 사용될 수 있다. 공간해상도 30 m 급의 Landsat 위성 자료를 이용하여 0.0625 mm 입자 기준에 의한 조간대의 표층 퇴적상 분류를 한 연구가 몇 차례보고 된 바 있지만, 스펙트럴 값만으로 퇴적상을 분류하기 위해서는 몇 가지 문제점이 따른다. 첫째는 점이적으로 변하는 조간대에서 입도와 위성자료 공간해상도와의 스케일 차이로 인한 mixed pixel(mixel)을 어떻게 분류할 것인가 이고 두 번째는 입도 요인 이외의 조간대 환경요인을 어떻게 고려해야 되느냐 하는 것이다. mixel에 대한 대안으로 4 m 공간해상도의 IKONOS 영상을 이용하였으며, 입도 이외의 다른 환경 요인은 조간대 지형과 조류로 (tidal channel)를 파악하여 퇴적상의 특성과 비교하였다. IKONOS를 이용한 조간대 퇴적상 분류 결과는 현장 조사 자료와 잘 일치하였으며 지형적으로 높고 조류로가 발달한 부분에 이질 퇴적상이 위치하는 것을 알 수 있었다. 이 연구는 IKONOS와 같은 공간해상도를 갖는 KOMPSAT II 위성이 2004년 진수되어 서해조간대 지역에 대해 다시기의 많은 영상을 확보할 수 있다면 조간대의 지형변화와 생태계 변화 등의 조간대 모니터링 연구에 활용되어 연안의 종합적이고 효율적인 관리에 활용될 수 있을 것으로 생각된다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.89-96
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• 2009

In this paper, we propose an efficient deinterlacing algorithm which is an edge dependent interpolation based on edge direction refinement. The conventional edge dependent interpolation algorithms have a visually better performance than any other Intra-field deinterlacing algorithms. However they are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method detects edge direction of around interpolated pixel and refines the edge direction using weighted median filter. Simulation results have shown the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.9-17
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• 2007

Feature based stereo matching is an effective way to perform 3D building reconstruction. However, in urban scene, the cluttered background and various building structures may interfere with the performance of building reconstruction. In this paper, we propose a novel method to robustly reconstruct buildings on the basis of rectangle regions. Firstly, we propose a multi-scale linear feature detector to obtain the salient line segments on the object contours. Secondly, candidate rectangle regions are extracted from the salient line segments based on their local information. Thirdly, stereo matching is performed with the list of matching line segments, which are boundary edges of the corresponding rectangles from the left and right image. Experimental results demonstrate that the proposed method can achieve better accuracy on the reconstructed result than pixel-level stereo matching.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.66.2-66.2
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• 2013

In this study, we present a pore-selection technique to estimate the size of pore. The estimation of the size of pore is important to examine the temporal evolution of size itself and corresponding intensity. The size of pore is typically estimated by applying the intensity threshold technique to the fixed box which contains the entire pore. The typical method has disadvantages in the following circumstances; there are small features near the pore or the image has low spatial resolution. In the former, it is difficult to define a box containing the pore only, excluding the small features near the pore. In the latter, the background and threshold intensity are insignificant due to the insufficient number of pixel in the box. To avoid these difficulties, we use a pore-selection technique which is simply based on the measurement of distances from the pore center. In addition, we will discuss the advantage of the technique for the imaging spectrograph data like the NST FISS.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.326-328
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• 2000

The paper proposes the scheme of skew detection for Thai printed document images by using linear regression algorithm. It intends to use with the Thai character recognition systems to reduce the skew detection time. This scheme begins by finding the center of gravity of a document image. This point is used as the starting point for gathering data in the scheme. The data is obtained by scanning incrementally one pixel in vertically with the width of 20-pixels. After the scanning process, if data Is different from it's neighbor more than ${\pm}$ 15 pixels, it will be considered as noise or data in other lines and will be deleted. The last step is the operation by using linear regression algorithm on these selected data and the skew angle will be obtained. The proposed method has been tested with 45 document images with different fonts, sizes and skew angles. The experiment results show that the proposed method can detect the skew angle with the error of less then one degree. The average processing time is about 19 times faster than that of the Hough Transform method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.148-149
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• 2008

As infrared light is radiated, the CMOS Readout IC (ROIC) for the microbolometer type infrared sensor detects voltage or current when the resistance value in the bolometer sensor varies. One of the serious problems in designing the ROIC is that resistances in the bolometer and reference resistor have process variation. This means that each pixel does not have the same resistance, causing serious fixed pattern noise problems in sensor operations. In this paper, Reference resistor compensation technique was proposed. This technique is to compensate the reference resistance considering the process variation, and it has the same reference resistance value as a bolometer cell resistance by using a comparator and a cross coupled latch.