• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.72-75
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• 2008

Image segmentation techniques becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Seeded Region Growing (SRG) and Edge Information. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying SRG. Finally the region merging process, using region adjacency graph (RAG), was carried out to get the final segmentation result. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.98-108
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• 2023

This paper is an attempt to design segmentation method based on fully convolutional networks (FCN) and attention mechanism. The first five layers of the Visual Geometry Group (VGG) 16 network serve as the coding part in the semantic segmentation network structure with the convolutional layer used to replace pooling to reduce loss of image feature extraction information. The up-sampling and deconvolution unit of the FCN is then used as the decoding part in the semantic segmentation network. In the deconvolution process, the skip structure is used to fuse different levels of information and the attention mechanism is incorporated to reduce accuracy loss. Finally, the segmentation results are obtained through pixel layer classification. The results show that our method outperforms the comparison methods in mean pixel accuracy (MPA) and mean intersection over union (MIOU).

• Journal of information and communication convergence engineering
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• 제12권1호
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• pp.60-65
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• 2014

This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.483-496
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• 2005

We consider the power law process which is assumed to have multiple changepoints. We propose a binary segmentation procedure for locating all existing changepoints. We select one model between the no-changepoints model and the single changepoint model by the Bayes factor. We repeat this procedure until no more changepoints are found. Then we carry out a multiple test based on the Bayes factor through the intrinsic priors of Berger and Pericchi (1996) to investigate the system behaviour of failure times. We demonstrate our procedure with a real dataset and some simulated datasets.

• International Journal of Internet, Broadcasting and Communication
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• 제10권3호
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• pp.73-80
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• 2018

This study introduces an interactive drawing system, a tool that allows user to sketch and draw with his own intentions. The proposed system enables the user to express more creatively through a tool that allows the user to reproduce his original idea as a drawing and transform it using his body. The user can actively participate in the production of the artwork by studying the unique formative language of the spectator. In addition, the user is given an opportunity to experience a creative process by transforming arbitrary drawing into various shapes according to his gestures. Interactive drawing systems use the segmentation of the drawing image as a way to extend the user's initial drawing idea. The system includes transforming a two-dimensional drawing into a volume-like form such as a three-dimensional drawing using image segmentation. In this process, a psychological space is created that can stimulate the imagination of the user and project the object of desire. This process of drawing personification plays a role of giving the user familiarity with the artwork and indirectly expressing his her emotions to others. This means that the interactive drawing, which has changed to the emotional concept of interaction beyond the concept of information transfer, can create a cooperative sensation image between user's time and space and occupy an important position in multimedia society.

• 한국멀티미디어학회논문지
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• 제8권5호
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• pp.651-659
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• 2005

본 논문에서는 무제약 필기체 한글 분할을 위하여 기존 방법들에서 제시된 적이 없는 문자간 여백에서 가상 네트워크 탐색 시스템을 이용하는 새로운 방법을 설계하고 구현하였다 제안된 방법은 다양한 필기자들이 제한 없이 쓰여진 모든 문자들에 대하여 적용이 가능하도록 설계되었고, 또한 문자간 여백에서 생성되는 가상 네트워크의 경로를 이용함으로서 꺾은선 형태의 다양한 분할경로를 얻을 수 있도록 설계되었다. 또한 탐색 시스템을 구현하는 과정에서 분할대상 블록의 길이에 따른 탐색 윈도우를 달리 적용함으로서 원하지 않는 영역에서 분할경로가 생성되는 것을 방지하였다 본 논문에서 제안하는 가상 네트워크 탐색 시스템에 대해 임의의 필기자들로 부터 자체적으로 수집한 800여개의 데이터를 대상으로 실험을 수행한 결과, 중첩되거나 접촉된 문자들을 포함하여 전체적으로 $91.4\%$ 정도의 분할 정확도를 얻을 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권4호
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• Journal of Information Processing Systems
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• 제9권1호
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• pp.117-140
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• 2013

Hindi is the most widely spoken language in India, with more than 300 million speakers. As there is no separation between the characters of texts written in Hindi as there is in English, the Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate. In this paper we propose an OCR for printed Hindi text in Devanagari script, using Artificial Neural Network (ANN), which improves its efficiency. One of the major reasons for the poor recognition rate is error in character segmentation. The presence of touching characters in the scanned documents further complicates the segmentation process, creating a major problem when designing an effective character segmentation technique. Preprocessing, character segmentation, feature extraction, and finally, classification and recognition are the major steps which are followed by a general OCR. The preprocessing tasks considered in the paper are conversion of gray scaled images to binary images, image rectification, and segmentation of the document's textual contents into paragraphs, lines, words, and then at the level of basic symbols. The basic symbols, obtained as the fundamental unit from the segmentation process, are recognized by the neural classifier. In this work, three feature extraction techniques-: histogram of projection based on mean distance, histogram of projection based on pixel value, and vertical zero crossing, have been used to improve the rate of recognition. These feature extraction techniques are powerful enough to extract features of even distorted characters/symbols. For development of the neural classifier, a back-propagation neural network with two hidden layers is used. The classifier is trained and tested for printed Hindi texts. A performance of approximately 90% correct recognition rate is achieved.

• 대한전자공학회논문지SP
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• 제38권5호
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• pp.518-528
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• 2001

본 논문에서는 먼저 영역 기반 부호화를 위한 새로운 결합 분할 척도를 정의하고 이를 이용한 새로운 영상 분할 알고리즘을 제안한다. 결합 분할 척도는 기존의 밝기 분할 척도, 움직임 분할 척도 및 제안한 변화 검출기로부터 정의되는 변화 분할 척도의 가중 합으로 구성된다. 변화 분할 척도는 기존의 변화 검출기의 결과 영상에 포함되어있는 많은 부정확한 요소들을 제거하기 위하여 수리 형태학에 기반한 녹임 필터링된 영상으로부터 한 화소와 이와 인접한 화소간의 변화 차의 절대값으로 정의된다. 변화 분할 척도는 움직임이 있는 이동체 영역과 배경 영역간의 정차한 분할을 하는데 있어서 효과적인 분할 척도로 사용될 수 있다. 그러므로 제안한 결합 분할 척도는 영역 기반 영상압축의 영상 분할과정에서 추정된 움직임 정보가 부정확하고, 움직임이 있는 이동체 영역과 배경 영역간의 경계 부분에서의 밝기가 유사하더라도 이들간의 경계를 정확히 분할할 수 있다.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1986년도 추계학술발표회 논문집
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• pp.186-190
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• 1986

This paper describes a way of implementing the segmentation of 128*128 pixel images to be used as the inputs. to a real-time automatic video tracker. The suggested method uses the lowest valley-value of the computed intensity historgram with 16 levels. This method improves smoothing effects and also significantly reduces hardware requirements. Entire segmentation process is caried out in 10msec thus making a real time application possible.