• 복식
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• 제54권3호
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• pp.13-25
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• 2004

The purpose of this study was to show the analysis system and the expression which is applied to fashion illustration by three major components in visual sign, metaphor and metonymy. The results of this study were as follows : Firstly, metaphor in qualisign of syntactics was revealed as a color such as realistic description, a pattern such as clothing of figure. etc. Metonymy was revealed as a social and cultural background color, a concept pattern. etc. In sinsign of syntactics. metaphor was revealed as a human body, non-human body and metamorphosis human body and metonymy as a human body and non-human body. In legisign of syntactics, the metaphor by perspective was used for a fantasy of space. and the metonymy was revealed as a color perspective representation, etc. The degree of change of texture was revealed as a metaphor and metonymy of gradation. And conventional custom sign was almost revealed in metaphor. Secondly, semantics showed about fashion image as juxtaposition of two similar objects in metaphor and as real description and simplification in metonymy Alternative fashion image in semantics was presented as a object related to fashion image. Conventional symbolic sign was presented as a role to clarify a fashion message in metaphor. Thirdly, the metaphorical and metonymical expression in pragmatics were usually presented as drawing and painting.

• 제어로봇시스템학회논문지
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• 제2권1호
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• pp.26-34
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• 1996

One of the challenging tasks in visual inspection using CCD camera is to identify surface defects in an image with complex textured backgeound. In microscopic view, the surface of real objects shows regular or random textured patterns. In this paper, we present a visual inspection algorithm to extract abnormal surface defects in an image with textured background. The algorithm uses the space and frequency information at the same time by introducing the Dominant Frequency Map(DFM) which can describe the frequency characteristics of every small local region of an input image. We demonstrate the feasibility and effectiveness of the method through a series of real experiments for a 14" TV CRT mold. The method successfully identifies a variety of infinitesimal defects, whose size is larger than $50\mu\textrm{m}$, of the mold. The experimental results show that the DFM based method is less sensitive to the environmental changes, such as illumination and defocusing, than conventional vision techniques.ques.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1230-1242
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• 1993

In a case of mushroom (Lentinus Edodes L.) , visual features are crucial for grading and the quantitative evaluation of the growth state. The extracted quantitative visual features can be used as a performance index for the drying process control or used for the automatic sorting and grading task. First, primary external features of the front and back sides of mushroom were analyzed. And computer vision based algorithm were developed for the extraction and measurement of those features. An automatic thresholding algorithm , which is the combined type of the window extension and maximum depth finding was developed. Freeman's chain coding was modified by gradually expanding the mask size from 3X3 to 9X9 to preserve the boundary connectivity. According to the side of mushroom determined from the automatic recognition algorithm size thickness, overall shape, and skin texture such as pattern, color (lightness) ,membrane state, and crack were quantified and measured. A portion of t e stalk was also identified and automatically removed , while reconstructing a new boundary using the Overhauser curve formulation . Algorithms applied and developed were coded using MS_C language Ver, 6.0, PC VISION Plus library functions, and VGA graphic function as a menu driven way.

• 한국멀티미디어학회논문지
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• 제20권12호
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• pp.1865-1873
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• 2017

The feature-based visual SLAM requires 3D positions for the extracted feature points to perform 3D-2D motion estimation. LiDAR can provide reliable and accurate 3D position information with low computational burden, while stereo camera has the problem of the impossibility of stereo matching in simple texture image region, the inaccuracy in depth value due to error contained in intrinsic and extrinsic camera parameter, and the limited number of depth value restricted by permissible stereo disparity. However, the sparsity of LiDAR data may increase the inaccuracy of motion estimation and can even lead to the result of motion estimation failure. Therefore, in this paper, we propose three interpolation methods which can be applied to interpolate sparse LiDAR data. Simulation results obtained by applying these three methods to a visual odometry algorithm demonstrates that the selective bilinear interpolation shows better performance in the view point of computation speed and accuracy.

• 한국생산제조학회지
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• 제24권4호
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• pp.455-462
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• 2015

A feature line is a visually noticeable creased line on outer automotive panels. Feature lines play an important role in creating a good impression of a car. Even though the manufacturing quality of feature lines is important, it is difficult to achieve the designed shape owing to the springback of sheet metal. The current study presents five methods of making samples that will be used in a visual experiment to discover a quality control quantitative manufacturing allowance for feature lines. Measurement and inspection methods for the samples are also presented. The results show that plunge machining is the most accurate way to make the desired shape, and that wrapping the machined surface with sheet film is an appropriate way to emulate the roughness and visual texture of the painted outer panels of a car.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1511-1514
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• 2002

This paper presents content adaptive image watermark embedding using stochastic visual model based on multiwavelet transform. To embedding watermark, the original image is decomposed into 4 levels using a discrete multiwavelet transform, then a watermark is embedded into the JND(just noticeable differences) of the image each subband. The perceptual model is applied with a stochastic approach fer watermark embedding. This is based on the computation of a NVF(noise visibility function) that have local image properties. The perceptual model with content adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the JND. This method uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The experiment results of simulation of the proposed watermark embedding method using stochastic visual model based on multiwavelet transform techniques was found to be excellent invisibility and robustness.

• 한국주거학회논문집
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• 제23권5호
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• pp.95-102
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• 2012

We studied in order to find out suitable amounts of board by visual effects to establish indoor boards and human psychological effects by several board designs. Thirty students of C university were tested in constant temperature/humidity room and interviewed after tests. The experimental visual images were projected from 54' TV. As a result, the board length that showed high preference and satisfaction was the 90cm both horizontal and vertical direction. We found that vertical board gave an impression of a linear and narrow shape and the horizontal board gave wide space and cool feeling from psychological analytical study. The factors affecting satisfaction in horizontal direction were refreshing, intimacy, beauty, area, splendor and those in vertical direction were a sense of security, beauty, texture, intimacy, continuity, extensity, natural feeling. We got 5 factors from the result of factor analysis in order to get psychological factor axis. Those were pleasantness, artificiality, openness, dynamics, refinement. By multiple regression analysis, the factor pleasantness had the highest impact on visual satisfaction on scenary. The study on psychological factor difference by analysis of variance showed that psychologically feeling amount about pleasantness, artificiality, dynamics, refinement, and openness had statistically meaningful difference despite of board direction. We found that the 90cm had a tendency as a changing point leading image change by the investigative analysis of board direction based on factor points.

• Journal of Biosystems Engineering
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• 제19권2호
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

• 한국어교육
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• 제29권3호
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• pp.325-344
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• 2018

The purpose of this study is to summarize PWIM (Picture Words Inductive Model) which is one of learner-centered vocabulary teaching-learning models, and suggest ways to implement them in Korean language education. The pictures that are used in the Korean language education field help visualize the specific shape, color, and texture of the vocabulary that is the learning target; thus, helping beginner learners to recognize the meaning of the sound. Visual material stimulates the intrinsic schema of the learner and not only becomes a 'bridge' connecting the mother tongue and the Korean language, but also reduces difficulty in learning a foreign language because of the ambiguity between meaning and sound in Korean and all languages. PWIM shows commonality with existing learning methods in that it uses visual materials. However, in the past, the teacher-centered learning method has only imitated the teacher because the teacher showed a piece-wise, out-of-life photograph and taught the word. PWIM is a learner-centered learning method that stimulates learners to find vocabulary on their own by presenting visual information reflecting the context. In this paper, PWIM is more suitable for beginner learners who are learning specific concrete vocabulary such as personal identity (mainly objects), residence and environment, daily life, shopping, health, climate, and traffic. The purpose of this study was to develop a method of using PWIM suitable for Korean language learners and teaching procedures. The researchers rearranged the previous research into three steps: brainstorming and word organization, generalization of semantic and morphological rules of extracted words, and application of words. In the case of PWIM, you can go through all three steps at once. Otherwise, it is possible to divide the three steps of PWIM and teach at different times. It is expected that teachers and learners using the PWIM teaching-learning method, which uses realistic visual materials, will enable making an effective class together.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.230-240
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• 2022

Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.