• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.126-129
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• 2008

In this paper, we proposed a method extracting an object from background of the satellite image. The image segmentation techniques have been widely studied for the technology to segment image and to synthesis segment object with other images. Proposed algorithm is to perform the edge detection of a selected object using genetic algorithm. We segment region of object based on detection edge using watershed algorithm. We separated background and object in indefinite region using gradual region merge from segment object. And, we make GUI for the application of the proposed algorithm to various tests. To demonstrate the effectiveness of the proposed method, several analysis on the satellite images are performed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.449-452
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• 2003

This paper propose a extracting method of the region for image using segmentation and edge information. First propose algorithm extract information using canny edge detector and the image was divided by watershed segmentation. And it extract the mage with edge information by merging region. Finally we compare the proposed method with levelset method. In the result proposed method not only extract the image with accurate region but also reduce operation time.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2012년도 춘계학술발표대회논문집
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• pp.40-42
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• 2012

Colorization is a method using computer to add color to a black and white image automatically. The input is a grayscale image and some representative pixels (RPs). The RPs contain the color information for the image, and it indicates each region's color information. Colorization-based coding is a novel way for lossy image compression, it decodes a color image to get grayscale image and extracts RPs from the image. Because RPs decides the region's color and we also want small data size for image compression, form this viewpoint the paper proposes a way to get better and fewer RPs based on watershed segmentation. According to the segmentation result we also improve the original chrominance blending colorization method to save decode time and get better reconstruct image.

• 대한전자공학회논문지SP
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• 제43권5호
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• pp.30-36
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• 2006

변형된 면적기반영역선별 기법으로 문자영상 속에 내재되어 있던 영역 분할을 회복하는 새로운 기법을 제안한다. 정보영역과 바탕영역으로 양분되어 있는 이진 원영상에 비해 오염 및 훼손으로 관측영상은 얼룩점과 잡음이 전체 영상에 섞여 다수의 크고 작은 영역들이 혼재된 그레이스케일 형태가 된다. 이러한 영상을 종래의 문턱치 처리나 확률적 기법으로 영역 분할하려면 이진영상으로 전환시킴에 의한 영역 형태 변형 문제가 발생한다. 이 문제를 최소화하기 위해 마름모꼴 블록을 채택한 반복조건부양식(iterated conditional mode, ICM) 기법으로 이진 영상을 구현하여 일차적으로 영역들의 집합으로 분류하였다. 그 다음 현재고려중인 화소에서 화소의 영역형성 판별과 영역의 면적을 산출하였다. 이를 전체 화소에 걸쳐 순차적으로 확산하여 해당영역들의 정보영역으로의 귀속 여부를 선택적으로 판정 분할함으로 정보영역 본래 형태를 복원하였다. 이 때 지정 영역들의 산출 면적들은 하나의 집합으로 배속 정렬되며 확률처리로 얻은 판별 파라미터 값에 의해 선별된다. 그레이스케일 탁본영상을 대상으로 종래의 문턱치 영역분할 기법과 ICM 기법도 함께 실험하였다. 그 결과 종래의 기법에 비해 우수한 영역분할 효과를 얻을 수 있었다.

• Journal of Electrical Engineering and information Science
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• 제3권2호
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• pp.230-238
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• 1998

When size and shape of moving object have been changed, a correlator often accumulates walk-off error. A success of correlation-based tracking largely depends on choosing suitable window size and position and thus transferring the proper reference image to the next frame. For this, we propose the Adaptive Window Algorithm with Four-Direction Sizing Factors (AWA-FSF) for fast adjusting a reference region to enhance reliability of correlation-based image tracking in complex cluttered environments. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, we can minimize the influence of complex background and clutter. In addition, we can finely tune the center point of the reference image repeatedly after main tracking process. Thus we have increased stability and reliability of correlation-based image tracking. We tested performance of the AWA-FSF using 45 real image sequences made of over 3400 images and had the satisfied results for most of them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4386-4404
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• 2016

Most existing salient object detection algorithms commonly employed segmentation techniques to eliminate background noise and reduce computation by treating each segment as a processing unit. However, individual small segments provide little information about global contents. Such schemes have limited capability on modeling global perceptual phenomena. In this paper, a novel salient object detection algorithm is proposed based on region merging. An adaptive-based merging scheme is developed to reassemble regions based on their color dissimilarities. The merging strategy can be described as that a region R is merged with its adjacent region Q if Q has the lowest dissimilarity with Q among all Q's adjacent regions. To guide the merging process, superpixels that located at the boundary of the image are treated as the seeds. However, it is possible for a boundary in the input image to be occupied by the foreground object. To avoid this case, we optimize the boundary influences by locating and eliminating erroneous boundaries before the region merging. We show that even though three simple region saliency measurements are adopted for each region, encouraging performance can be obtained. Experiments on four benchmark datasets including MSRA-B, SOD, SED and iCoSeg show the proposed method results in uniform object enhancement and achieve state-of-the-art performance by comparing with nine existing methods.

• Journal of Advanced Marine Engineering and Technology
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• 제28권4호
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• pp.587-592
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• 2004

Pixel classification is one of basic issues of image processing. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time, a pixel classification scheme based on image information scales is proposed. The proposed method is overcome that computation amount become greater and contents easily get turned. And image directional scales has excellent anti-noise performance. In the result of experiment. good efficiency is showed compare with other methods.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.285-289
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• 1999

A processing system to produce cloud-free composite image data set was developed. In the process, a fine geometric correction based on orbit parameters and ground control points and radiometric correction based on 6S code are applied. Presently, by using AVHRR image data received at Tokyo, Okinawa, Ulaanbaatar and Bangkok, data set of 10 days composite images covering almost whole Asian region.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2351-2354
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• 2003

A new transform coder for arbitrarily shaped image segments is proposed. In the encoder, a block-based DCT is applied to the resulting image block after shifting pixels within the image segment to block border and padding the mean value of the pixels to empty region. For reducing the transmission bit rate, the transform coefficients located in padded region are truncated and only the remaining transform coefficients are transmitted to the decoder. In the decoder, the transform coefficients truncated in the encoder are recovered using received transform coefficients and a block-based inverse DCT is performed.

• 한국군사과학기술학회지
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• 제11권4호
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• pp.107-115
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• 2008

Accurate extraction of traversable region is a critical issue for autonomous navigation of unmanned ground vehicle(UGV). This paper introduces enhanced extraction of traversable region by combining scene clustering with 3D world modeling using CCD(Charge-Coupled Device)/IR(Infra Red) image. Scene clustering is developed with K-means algorithm based on CCD and IR image. 3D world modeling is developed by fusing CCD and IR stereo image. Enhanced extraction of traversable regions is obtained by combining feature of extraction with a clustering method and a geometric characteristic of terrain derived by 3D world modeling.