• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.47-52
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• 2007

Conventional pixel based region segmentation methods have problems of long processing time and incorrect region split on account of performing region split through comparison of neighboring pixels. In this paper, we propose the method which segments a large size of satellite image effectively using modified centroid linkage method. This method is a sort of region split and merge. The proposed method merges pixels and makes them as a new region through only two directional comparing the current positioning pixel with neighbor ones, if they are satisfied with given conditions. Therefore, this method has less comparing time than the cases of previous ones. The experimental result shows that the proposed method is very efficient because of having less processing time and more exact segmented regions than the previous ones.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.449-454
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• 2020

We propose an improved de-interlacing method that converts the interlaced images into the progressive images by one field. In the first, Inter-pixel values are calculated by applying Newton's forward difference, backward difference interpolation from upper and lower 5 pixel values. Using inter-pixel values obtained from upper and lower 5 pixel values, it makes more accurate a direction estimate by applying the correlation between upper and lower pixel. If an edge direction is determined from the correlation, a missing pixel value is calculated into the average of upper and lower pixel obtained from predicted direction of edge. From simulation results, it is shown that the proposed method improves subjective image quality at edge region and objective image quality at 0.2~0.3dB as quantitative calculation result of PSNR, compared to previous various de-interlacing methods.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.5
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• pp.42-47
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• 1999

연속 계조도 영상을 이진 영상(하프톤 영상)으로 변환하는 하프톤 기법중 대표적인 두 방법은 순차적 디더법과 오차 확산법이 있다. 이 중에서 오차확산법은 예리한 하프톤 영상을 얻기위한 우수한 하프톤 기법으로 잘 알려져 있다. 그러나 알고리듬에 기인하는 여러 인공잡음들이 발생하므로 이를 개선하기 위한 방법으로 최적의 필터 계수를 얻기 위한 많은 연구가 진행되었다. 본 논문에서는 연속 계조도 입력 영상과 하프톤 영상사이의 양자화 오차를 영상에 적응적이며 최적으로 확산시키기 위해 양자화 오차를 초기 가능성의 퍼지 부분 집합으로 정의하였다. 이러한 퍼지 부분 집합의 중심화소에 대해 이웃한 화소의 오차 가능성을 고려한 후 FAM 규칙을 이용하여 각각 화소들의 오차 가능성을 영상에 따라 적응적으로 갱신하였으며 이를 원영상에 더하여 다시 양자화 과정을 번복하는 퍼지 이완 알고리듬을 이용한 오차 확산법을 제안하였다. 제안한 방법을 이용하여 얻은 결과를 최적 필터 계수를 구하기 위한 기존의 방법의 결과 영상과 비교 분석하였다.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.561-566
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• 2005

This paper presents a visual tracking algorithm for the golf swing motion analysis by using the information of the pixels of video frames and movement of the golf club to solve the problem fixed center point in model based tracking method. The model based tracking method use the polynomial function for trajectory displaying of upswing and downswing. Therefore it is under the hypothesis of the no movement of the center of gravity so this method is not for the amateurs. we proposed method using the information of pixel and movement, we first detected the motion by using the information of pixel in the frames in golf swing motion. Then we extracted the club head and hand by a properties of club shaft that consist of the parallel line and the moved location of club in up-swing and down-swing. In addition, we can extract the center point of user by tracking center point of the line between center of head and both foots. And we made an experiment with data that movement of center point is big. Finally, we can track the real trajectory of club head, hand and center point by using proposed tracking algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.933-935
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• 2015

Currently, image processing is being utilized in various fields and many studies on the image restoration is being progressed in order to eliminate the noise being generated during the process of transmitting, processing and storing of image. There are various types of noises included in the image according to the causes and types but AWGN is the most representative. In this paper, an algorithm was proposed which applies the variables differently according to the differences in surrounding pixels and central pixels within the local mask in order to mitigate the AWGN included in the image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1973-1980
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• 2014

Edge detection for such as image, lane and object recognition is important image processing method. And some traditional method for this, there are Sobel, Prewitt, Roberts, Laplacian, LoG(Laplacian of Gaussian) and so on. Characteristics of these methods are insufficient in the salt & pepper noise added image. In order to improve such a problem of conventional methods, in this paper, we proposed an algorithm applying the weighted mask for detecting an edge by setting the local mask centered on the adjacent of the central pixel if central pixel of the mask is non-noise, it is intactly set by element of estimated mask, after calculating estimated mask if it is noise.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.136-138
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• 2022

Edge detection includes information such as the shape, position, size, and material of an object with respect to an image, and is a very important factor in analyzing the characteristics of the image. Existing edge detection methods include Sobel edge detection filter, Roberts edge detection filter, Prewitt edge detection filter, and LoG (Lapacian of Gaussian) using secondary differentials. However, these methods have a disadvantage in that the edge detection results are somewhat insufficient because a fixed weight mask is applied to the entire image area. Therefore, in this paper, we propose an edge detection algorithm that increases edge detection characteristics by considering the center pixel in the mask. In addition, in order to confirm the proposed edge detection performance, it was compared through simulation result images.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.34-43
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• 2010

Texture information plays an important role in object recognition and classification. To perform an accurate classification, the texture feature used in the classification must be highly discriminative. This paper presents a novel texture descriptor for texture-based image retrieval and its application in Computer-Aided Diagnosis (CAD) system for Emphysema classification. The texture descriptor is based on the combination of local surrounding neighborhood difference and centralized neighborhood difference and is named as Combined Neighborhood Difference (CND). The local differences of surrounding neighborhood difference and centralized neighborhood difference between pixels are compared and converted into binary codewords. Then binomial factor is assigned to the codewords in order to convert them into high discriminative unique values. The distribution of these unique values is computed and used as the texture feature vectors. The texture classification accuracies using Outex and Brodatz dataset show that CND achieves an average of 92.5%, whereas LBP, LND and Gabor filter achieve 89.3%, 90.7% and 83.6%, respectively. The implementations of CND in the computer-aided diagnosis of Emphysema is also presented in this paper.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1171-1176
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• 2003

In this paper, we propose an effective bar code detection algorithm using the feature analysis and the labeling. After computing the direction of pixels using four line operators, we obtain the histogram about the direction of pixels by a block unit. We calculate the difference between the maximum value and the minimum value of the histogram and consider the block that have the largest difference value as the block of the bar code region. We get the line passing by the bar code region with the selected block but detect blocks of interest to get the more accurate line. The largest difference value is used to decide the threshold value to obtain the binary image. After obtaining a binary image, we do the labeling about the binary image. Therefore, we find blocks of interest in the bar code region. We calculate the gradient and the center of the bar code with blocks of interest, and then get the line passing by the bar code and detect the bar code. As we obtain the gray level of the line passing by the bar code, we grasp the information of the bar code.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.676-678
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• 2016

Noise occurs in the process of obtaining, transmission, and processing in image processing systems and these noises lower the resolution of image and cause visual errors. Currently, a representative filter to remove salt and pepper noise is SMF(standard median filter) but it is inadequate in preserving edge as the noise field expands. Therefore, for salt and pepper noise enviroment, the study suggested and algorithm that are places with original pixel when the central pixel is non-noise and process by applying weighted value on areas with less local mask pixel changes when there is noise.