• Journal of Digital Convergence
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• v.11 no.12
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• pp.459-465
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• 2013

This paper is a study on an object extraction method which using color features of an object and background in the image. A human recognizes an object through the color difference of object and background in the image. So we must to emphasize the color's difference that apply to extraction result in this image. Therefore, we have converted to HSV color images which similar to human visual system from original RGB images, and have created two each other images that applied Median Filter and we merged two Median filtered images. And we have applied the Mean Shift algorithm which a data clustering method for clustering color features. Finally, we have normalized 3 image channels to 1 image channel for binarization process. And we have created object map through the binarization which using average value of whole pixels as a threshold. Then, have extracted major object from original image use that object map.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.194-202
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• 2003

To convert printed images into electronic ones automatically, it requires region analysis of document images and character recognition. In these, regional analysis segments document image into detailed regions and classifies thee regions into the types of text, picture, table and so on. But it is difficult to classify the text and the picture exactly, because the size, density and complexity of pixel distribution of some of these are similar. Thu, misclassification in region analysis is the main reason that makes automatic conversion difficult. In this paper, we propose region analysis method that segments document image into text and picture regions. The proposed method solves the referred problems using one dimensional median filter based method in text and picture classification. And the misclassification problems of boldface texts and picture regions like graphs or tables, caused by using median filtering, are solved by using of skin peeling filter and maximal text length. The performance, therefore, is better than previous methods containing commercial softwares.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.81-89
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• 1999

Image obtained by incomplete communication always include noise, blur and distortion, etc. In this paper, we propose and apply the new spatial filter algorithm, called an optimal adaptive generalized stack filter(AGSF), which optimizes adaptive generalized stack filter(AGSF) using neural network weight learning algorithm of back-propagation learning algorithm for improving noise removal and edge preservation rate. AGSF divides into two parts: generalized stack filter(GSF) and adaptive multistage median filter(AMMF), GSF improves the ability of stack filter algorithm and AMMF proposes the improved algorithm for reserving the sharp edge. Applied to neural network theory, the proposed algorithm improves the performance of the AGSF using two weight learning algorithms, such as the least mean absolute(LAM) and least mean square (LMS) algorithms. Simulation results of the proposed filter algorithm are presented and discussed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.2
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• pp.71-79
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• 2008

This study proposed a content-based image retrieval system that uses RGB maximum frequency indexing and BW clustering in order to deal with existing retrieval errors using histogram. We split RGB from RGB color images, obtained histogram which was evenly split into 32 bins, calculated and analysed pixels of each area at histogram of R, G, B and obtained the maximum value. We indexed the color information obtained, obtained 100 similar images using the values, operated the final image retrieval system using the total number and distribution rate of clusters. The algorithm proposed in this study used space information using the features obtained from R, G, and B and clusters to obtain effective features, which overcame the disadvantage of existing gray-scale algorithm that perceived different images as same if they have the same frequencies of shade. As a result of measuring the performances using Recall and Precision, this study found that the retrieval rate and priority of the proposed algorithm are more outstanding than those of existing algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.805-813
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• 2002

Document image should be classified into detailed regions as text, picture, table and etc through the geometric layout analysis if paper documents can be converted automatically into electronic documents. However, complexity of the document layout and variety of the size and density of a picture are the reason to make it difficult to analyze the geometric layout of the document images. In this paper, we propose the method which have a better performance of the region segmentation and classifications, and the line extraction in the table region than the commercial softwares and previous methods. The proposed method can segment the document into detailed regions by using connected components method even if its layout is complex. This method also classifies texts and pictures by using separable median filter even. Though their size and density are diverse, In addition, this method extracts the lines from the table adapting one dimensional median filter to the each horizontal and vertical direction, even though lines are deformed or texts attached to them.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.49-52
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• 2003

본 논문에서는 실시간 감시 시스템의 응용분야를 위한 백그라운드 모델링과 업데이트 그리고 오브젝트 추출 시스템을 설계 구현한다. 일반적인 감시 시스템은 백그라운드의 모델링(background modeling)과 오브젝트의 검출(object detection), 오브젝트의 추적(tracking)으로 구성된다. 실시간 감시시스템을 가능하게 하기 위해서는 작은 시간 복잡도(low time complexity)로 백그라운드와 오브젝트를 검출할 수 있어야 하고 실외환경(outdoor)의 노이즈(noise)를 반영할 수 있어야 한다. 기존에는 빠른 백그라운드 모델링을 위해 분산, 평균, 최빈값 등을 사용한 연구들이 있었다. 이러한 방법들은 빠른 수행 속도를 보장하지만 노이즈를 오브젝트로 검출하는 문제점이 있다. 또 다른 연구 분야인 메디안(median) 검출 방법은 실외환경에 존재하는 노이즈 반영에 적합한 반면, 정렬(sorting) 연산에 많은 시간이 소요된다. 본 논문은 윈도우(Window) 기반의 러닝 윈도우 리스트(Running Window List)를 이용하여 메디안 정렬 시간을 최소화하고 실시간으로 백그라운드 모델링, 오브젝트 검출, 백그라운드 업데이트를 할 수 있는 방법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.922-924
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• 2015

Recently, the image processing technologies using the public media such as the film, TV, camera and advertisement have been rapidly developed. However, the deterioration occurs with the image in the process of data processing, transmission and storage, and the typical cause of such deterioration is the salt and pepper noise. Typical filters to remove the salt and pepper noise include CWMF(center weighted median filter) and AMF(adaptive median filter) but such filters bring more or less insufficient characteristics of noise removal and visual error as the noise density gets higher. Thus, this paper proposed the median filter which applied the local mask segmented to 4 areas in order to remove the salt and pepper noise effectively and used PSNR(peak signal to noise ratio) as a criterion of judgment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.274-276
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• 2015

The image processing is recognized as an important field as Internet develops. The image is deteriorated in the process of obtaining, storage and transmission with various causes. Many studies have been carried out to restore the image by mainly removing the impact of salt and pepper noise added to the image. Thus, this paper proposed a modified median filter using pixel distribution in order to remove the impact of salt and pepper noise added to the image and compared it with the current methods using PSNR(peak signal to n oise ratio) as a criterion of judgment for objective judgment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.989-995
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• 2013

Image degradation caused by the impulse noise is generated in the process of image transmission and so on. It has been studied by many researchers in order to remove these noise. The representative impulse noise removal method includes SM filter. Though SM filter will indicate errors by the increasing of impulse noise density. Therefore, in this paper, in order to preserve the edges of the image, and reduce the distortion of the image, an improved adaptive median filter algorithm is proposed. In the simulation results, the algorithm showed excellent results in all several areas, and the PSNR is used as the criterion of evaluation.