• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.827-829
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• 2013

생체인식을 통한 개인 인증방법에는 지문인식과, 홍채인식 등이 활발하게 연구가 진행되고 있다. 본 논문에서는 생체인식을 통한 개인 인증 방법 중 우측 검지손가락 정맥을 이용한 방법을 사용하였다. 적외선 LED 8개를 이용하여 적외선을 손가락에 투과하여 CMOS카메라를 통하여 영상을 획득하는 정맥인식장치를 개발하고 영상을 채집한다. ROI영역을 추출하여 손가락 정맥인식을 위한 영상부분만 추출한다. 추출된 영상을 통하여 미디언 필터를 이용하여 noise를 제거하고 히스토그램 평활화를 통한 정맥영역을 부각시킨다. 특히 지역적 히스토그램 평활화를 통해서 보다 정확한 정맥의 영역을 찾는다. 지역적 히스토그램 평활화를 통한 영상을 이진화를 시키고 세선화를 통해서 이후 패터매칭을 통한 개인 인증방법에 대한 전처리 영상을 구한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.80-87
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• 2017

This paper proposes a pre-processing algorithm to improve perceptual video coding efficiency which decomposes an input frame via a sub-band decomposition, and suppresses only high frequency band(s) having low visual sensitivity. First, we decompose the input frame into several frequency subbands by a linear sub-band decomposition. Next, high frequency subband(s) which is rarely recognized by human visual system (HVS) is suppressed by applying relatively small gain(s). Finally, the high frequency suppressed frame is compressed by a specific video encoder. We can find from the experimental results that if comparing before-use and after-use of the proposed pre-processing prior to the encoder, no visual difference is shown. Also, the proposed algorithm achieves bit-saving of 13.12% on average in a H.264 video encoder.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1992.06a
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• pp.447-451
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• 1992

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.162-165
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• 2018

In this paper, we propose a pre-processing procedure to obtain scene change information using spatial down-scaled input image for efficient encoding of super-high resolution image and propose a reconstruction of reference picture list in inter-picture prediction using this information. The experimental results show that the proposed method improves the BD-Rate by 0.44% and reduces encoding time by 12.46% when compared to HM 16.12.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.85-94
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• 2019

Warhead and debris show the different micro-Doppler frequency shape in the spectrogram because of the different micro motion. So we can classify them using the micro-Doppler features. In this paper, we classified warhead and debris in the separation phase using CNN(Convolutional Neural Networks). For the input image of CNN, we used micro-Doppler spectrogram. In addition, to improve classification performance of warhead and debris, we applied the preprocessing using CA-CFAR to the micro-Doppler spectrogram. As a result, when the preprocessing of micro-Doppler spectrogram was used, classification performance is improved in all signal-to-noise ratio(SNR).

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.389-392
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• 2003

MRI 영상은 뇌의 해부학적 정보와 기능적인 정보를 제공하는 유용한 도구이다. MR 뇌 영상은 2차원 영상뿐만 아니라 3차원 영상도 임상적으로 중요하다. MR 영상에서 뇌영역의 추출방법으로는 형태학적인 방법, 히스토그램을 이용한 방법, 에지 정보를 이용한 방법, 지식 기반을 이용한 방법들이 있다. 본 논문에서는 region growing을 이용하여 MR 영상에서 뇌 영역을 추출하였다. 3차원 가시화를 위하여 오픈 소스인 VTK를 이용하여 Ray Casting 알고리즘으로 구현하였다. 그리고 의료영상에서 사용되는 각종 단면을 3차원 뇌 영상에서 재구성하였다. 256×256 크기의 71 뇌MR 영상 70장을 이용하여 실험하였다. 향후 연구과제로 MR 영상에서 뇌 영역추출방법과 원영상의 전처리 과정의 연구가 필요하다.

• Korean Journal of Remote Sensing
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• v.12 no.1
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• pp.26-42
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• 1996

The CCD Earth Images Experiment(CEIE) is one of the main payload of the KITSAT-1. Since it was launched on Oct. 10, 1992, the CEIE has taken more than 500 images on the Earth surface world-wide so far. An image from the space is very different from a feature on the real Earth surface due to various radiometric and geometric distortions. Preprocessing to remove those distortions has to take place before the images data are processed and analyzed further for various applications. This paper describes the procedure to perform preprocessing including radiometric and geometric correction.e-processing system. The GCP marking using this technique showed a sufficient accuracy for KITSAT1,2 narrow camera images.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.77-82
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• 2017

In this paper, a new security algorithm to recognize the type of the vehicle with the vehicle image as a input image is suggested. The vehicle recognition security algorithm is composed of five core parts, such as the input image, background removal, edge areas extraction, pre-processing(binarization), and the vehicle recognition. Therefore, the final recognition rate of the security algorithm for vehicle type recognition can be affected by the function and efficiency of each step. After inputting image into a gray scale image and removing backgrounds, the binarization is performed by extracting only the edge region. After the pre-treatment process for making outlines clear, the type of vehicles is categorized into large vehicles, passenger cars and motorcycles through the ratio of height and width of the vehicle.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.57-64
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• 2009

In this paper, We propose an highly efficient preprocessing technique for improving the performance of the crease extraction method, which can improve the accuracy of feature extraction within the fingerprint image. The proposed method applies the 1-dimensional directional slit for each pixel in fingerprint image. Once the direction of every pixel in crease candidate area is estimated, it is decomposed into different images depending on their direction. From the directional images, the crease clusters are estimated by utilizing the property of crease area. The proposed method finally extracts the crease from the crease clusters estimated from directional images.