• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.1005-1010
• /
• 1989

A refined version of automatic micro-organism recognition and identification method, 'O.I.S.M.2' is proposed in this paper, using image processing based on an expert system. This proposed method is based on the segmentation of the organism image, characterizing segment features, which are independent of individual size and length. Complicated shapes of organisms are divided into basic shape segments defined in this paper such as lines, circles, ovals etc. Organisms can then be expressed simply in a set of segments, regardless their individual differences.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.8
• /
• pp.1715-1721
• /
• 1997

Wavelet transform is not applicable to arbitrarily-shaped region (or object) in images, due to the nature of its global decomposition. In this paper, the arbitrarily-shaped wavelet transform(ASWT) is proposed in order to solve this problem and its properties are investigated. Computation complexity of the ASWT is also examined and it is shown that the ASWT requires significantly fewer computations than conventional wavelet transform, since the ASWT processes only the object region in the original image. Experimental resutls show that any arbitrarily-shaped image segment can be decomposed using the ASWT and perfectly reconstructed using the inverse ASWT.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.4
• /
• pp.125-132
• /
• 2021

As the layers of artificial neural network deepens, and the dimension of data used as an input increases, there is a problem of high arithmetic operation requiring a lot of arithmetic operation at a high speed in the learning and recognition of the neural network (NN). Thus, this study proposes a data dimensionality reduction method to reduce the dimension of the input data in the NN. The proposed Line-segment Feature Analysis (LFA) algorithm applies a gradient-based edge detection algorithm using median filters to analyze the line-segment features of the objects existing in an image. Concerning the extracted edge image, the eigenvalues corresponding to eight kinds of line-segment are calculated, using 3×3 or 5×5-sized detection filters consisting of the coefficient values, including [0, 1, 2, 4, 8, 16, 32, 64, and 128]. Two one-dimensional 256-sized data are produced, accumulating the same response values from the eigenvalue calculated with each detection filter, and the two data elements are added up. Two LFA256 data are merged to produce 512-sized LAF512 data. For the performance evaluation of the proposed LFA algorithm to reduce the data dimension for the recognition of handwritten numbers, as a result of a comparative experiment, using the PCA technique and AlexNet model, LFA256 and LFA512 showed a recognition performance respectively of 98.7% and 99%.

• Journal of Korea Multimedia Society
• /
• v.11 no.3
• /
• pp.292-300
• /
• 2008

An algorithm for detecting a line segment in an image is presented using incremental pixel extension. We use a different approach from conventional algorithms, such as the Hough transform approach and the line segment grouping approach. The Canny edge is calculated and an arbitrary point is selected among the edge elements. After the arbitrary point is selected, a base line approximating the line segment is calculated and edge pixels within an arbitrary radius are selected. A weighted value is assigned to each edge pixel, which is selected by using the error of the distance and the direction between the pixel and the base line. A line segment is extracted by Jilting a line using the weighted least square method after determining whether selected pixels are linked or delinked using the sum comparison of the weights. The proposed algorithm is compared with two other methods and results show that our algorithm is faster and can detect the real line segment.

• Journal of Korea Multimedia Society
• /
• v.15 no.12
• /
• pp.1430-1441
• /
• 2012

In this paper, we present an algorithm that quickly and effectively estimates orthogonal vanishing points in equirectangular images of urban environment. Our algorithm is based on the RANSAC (RANdom SAmple Consensus) algorithm and on the characteristics of the line segment in the spherical panorama image of the $360^{\circ}$ longitude and $180^{\circ}$ latitude field of view. These characteristics can be used to reduce the geometric ambiguity in the line segment classification as well as to improve the robustness of vanishing point estimation. The proposed algorithm is validated experimentally on a wide set of images. The results show that our algorithm provides excellent levels of accuracy for the vanishing point estimation as well as line segment classification.

• Journal of the Korea Society for Simulation
• /
• v.11 no.3
• /
• pp.35-48
• /
• 2002

In the work presented here, we describe a method to extract TrueType features for supporting letter recognition. Even if variously existing document processing techniques have been challenged, almost few methods are capable of recognize a letter associated with its TrueType features supporting OCR free, which boost up fast processing time for image text retrieval. By reviewing the mechanism generating digital fonts and birth of TrueType, we realize that each TrueType is drawn by its contour of the glyph table. Hence, we are capable of deriving the segment with density for a letter with a specific TrueType, defined by the number of occurrence over a segment width. A certain number of occurrence appears frequently often due to the fixed segment width. We utilize letter recognition by comparing TrueType feature library of a letter with that from input word images. Experiments have been carried out to justify robustness of the proposed method showing acceptable results.

• Journal of Korean Academy of Nursing
• /
• v.29 no.2
• /
• pp.383-392
• /
• 1999

Recently, the hospitals in Korea has positively changed one way or another. Therefore hospital managers must focus on the nurses' role in terms of consumers' perception of overall image of hospitals and the degree of satisfaction of the consumers. To achieve the purposes, the questionnaire was developed and distributed to 280 people who had a direct experience with nursing services subjected hospitals in Seoul at the time of screening. Among them, 229 responses were turned out to be useful and used for final analysis. The measurement instrument for hospital nursing service quality evaluation was modified from the SERVQUAL model originated from Parasuraman, Zeithaml, and Berry (1988). For data analysis, SPSS/PC and PC-MDS program were used. The results were as follows : 1) The perception map showed that the seven subjected hospitals were divided into three groups. It could be interpreted that the hospitals in the same group had a strong competitive relationships. Because the nursing services' scores of hospitals C and E were higher than those of other hospitals, they could be served as a benchmark for the other hospitals. 2) The marketing place of hospital nursing services was divided by four. Since service generally had a strong point in nearby service market segment. Aiming an nearby hospital nursing services market segment by the hospital nursing services department was regarded as a good repositioning strategy. 3) When consumers evaluated the quality of hospital nursing services, they were greatly affected by the hospitals' overall image or other characteristics. Therefore, for improving hospital's nursing services, hospital nursing services department requires a great deal of labor to improve hospitals' overall image or other characteristics.

• Journal of the Korea Computer Graphics Society
• /
• v.2 no.2
• /
• pp.21-28
• /
• 1996

The nature of complexity of medical images makes them difficult to segment using standard techniques. Therefore the usual approaches to segment images continue to predominantly involve manual interaction. But it tediously consumes a good deal of time and efforts of the experts. Hereby a nonmanual parameters estimation which can replace the manual interaction is needed to solve the problem of redundant manual works for an image segmentation. This paper attempts to estimate parameters for an image region segmentation using Scale Space Filtering. This attempt results in estimating the number of regions, their boundary and each representatives to be segmented 2-dimensionally and 3-dimensionally. Using this algorithm, we may diminish the problem of wasted time and efforts for finding prerequisite segmentation parameters, and lead the relatively reasonable result of region segmentation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2015.07a
• /
• pp.9-12
• /
• 2015

In this paper, we propose a new feature matching algorithm by modifying and combining the FAST(Features from Accelerated Segment Test) feature detector and SURF feature descriptor which is robust to the distortion of the given image. Scale space is generated to consider the variation of the scale and determine the candidate of features in the image robust to the noise. The original FAST algorithm results in many feature points along edges. To solve this problem, we apply the principal curvatures for refining it. We also use SURF descriptor to make it robust against the variations in the image by rotation. Through the experiments, it is shown that the proposed algorithm has better performance than the conventional feature matching algorithms even though it has much less computational load. Especially, it shows a strength for noisy images.

• The Research Journal of the Costume Culture
• /
• v.9 no.6
• /
• pp.818-829
• /
• 2001

The purposes of this study were to segment the men in twenties and thirties according to clothing benefits sought, and to develop a profile of each segment concerning shopping orientation, self·image, and importance of store attributes. The questionnaire was administered to men in twenties and thirties living in Seoul and data were analyzed by frequency, percentage, factor analysis, cluster analysis, and MANOVA(multivarite analysis of variance). By cluster analysis of clothing benefits sought, three groups were identified and labeled as: (1) the group of focusing the influence of other people and comfort clothing(31.7%): (2) the group of pursuing the fashion trend (48.1%); the group of pursuing the individuality(20.1%). Three groups were then compared through MANOVA on shopping orientation, importance of store attributes, and self-image. Significant differences were found among three groups on three variables. In general, the group of focusing the influence of other people and comfort clothing tended to be ostentatious and tended to wear comfortable clothing. The group of pursuing the fashion trend didn't show specific shopping orientation and just liked to follow the current fashion trend. The group of pursuing the individuality enjoyed the shopping and liked to buy the clothing which enhances the personal character.