• 유통과학연구
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• 제14권8호
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• pp.153-160
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• 2016

Purpose - The current distribution enterprises have realized the necessity for integrated and specialized images in their stores. From those reasons, visual merchandising has been considered as a powerful means towards brand value judgement as well as maximizing both brand and corporate identity. This research intends to study and discuss the current situations in Korean visual merchandising and its future concept setting. Based on the research findings, this paper tries to propose the basic concept for development strategies of visual merchandising in Korean distribution market. Although the studies on visual merchandising in Korean traditional markets have been continued, visual merchandisers have been distorted by display control centers in real situations. Therefore, this study tries to set both current and future concepts in visual merchandising for further discussions and a new complement formulation. Research design, data, and methodology - This study has investigated previous studies with the way of normative study by comparing, organizing concepts and relating terms on visual merchandising. In order to be an exact research, it seems to be more appropriate to analyze this study with a deductive analysis way rather than inductive as for getting the core of visual merchandising. Besides, this study changed the term 'visual merchandising' into 'VMD', and used it as an unified one. Results - Visual merchandising has an important key in retail planning. With focusing on organizing visual merchandising concepts, it should be adequate for domestic circumstances because there are various visual merchandising concepts with different perspectives. Thus, it is necessary to establish a concept including modern and Korean features through previous studies and data. Visual merchandising can be defined as followings. It enhances the value of shop images from visual aspects and conveys brand concepts effectively. Its task is to plan and manage products sales by combining three merchandising domains such as interior, display, and merchandising. Conclusions - There are some limitations on setting academic concepts in visual merchandising due to its features as to be taken in the field focused studies. More meaningful case studies should be performed as an area of future studies. Therefore, it is necessary to perform an effectiveness analysis on empirical visual merchandising state and present the course of development.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.410-414
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• 1996

A visual servoing algorithm is proposed for a robot with a camera in hand. Specifically, novel image features are suggested by employing a viewing model of perspective projection to estimate relative pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a, commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.

• 한국정밀공학회지
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• 제15권7호
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• pp.26-35
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• 1998

This paper presents a visual inspection algorithm looking for solder joint defects of IC chips on PCBs (Printed Circuit Boards). In this algorithm, seven features are proposed in order to categorize the solder joints into four classes such as normal, insufficient, excess, and no solder, and optimal back-propagation network is determined by error evaluation which depend on the number of neurons in hidden and out-put layers and selection of the features. In the end, a good accuracy of classification performance, an optimal determination of network structure and the effectiveness of chosen seven features are examined by experiment using proposed inspection algorithm.

• 한국멀티미디어학회논문지
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• 제25권10호
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• pp.1386-1394
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• 2022

As consumption of high-quality fruits increases and sales and packaging units become smaller, the demand for automatic fruit grading systems is increasing. Compared to other crops, the quality of fruit is determined by visual characteristics such as shape, color, and scratches, rather than just physical size and weight. Accordingly, this study presents a CNN model that can effectively extract and classify the visual features of fruits and a perceptron that classifies fruits using physical features, and proposes a stacking ensemble model that can effectively combine the classification results of these two neural networks. The experiments with AI Hub public data show that the stacking ensemble model is effective for grading fruits. However, the ensemble model does not always improve the performance of classifying all the fruit grading. So, it is necessary to adapt the model according to the kind of fruit.

• Journal of information and communication convergence engineering
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• 제22권1호
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• pp.56-63
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• 2024

Despite the rapid strides in content-based image retrieval, a notable disparity persists between the visual features of images and the semantic features discerned by humans. Hence, image retrieval based on the association of semantic similarities recognized by humans with visual similarities is a difficult task for most image-retrieval systems. Our study endeavors to bridge this gap by refining image semantics, aligning them more closely with human perception. Deep learning techniques are used to semantically classify images and retrieve those that are semantically similar to personalized images. Moreover, we introduce a keyword-based image retrieval, enabling automatic labeling of images in mobile environments. The proposed approach can improve the performance of a mobile device with limited resources and bandwidth by performing retrieval based on the visual features and keywords of the image on the mobile device.

• 제어로봇시스템학회논문지
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• 제7권9호
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• pp.758-765
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• 2001

본 논문에서는 랜드마트 정보 없이 장해물의 위치 정도 지도만 주어졌을 때 스테레오 시작(stereo vision)을 가진 이동로봇이 관측위치와 조명의 변화에도 강인한 시각 특징을 랜드마크로써 추출하는 수법을 제안한다. 장해물의편평한 면사에서 보다 안쪽영역에 존재하는 특징이 관측위치의 변화에 영향을 덜 받기 때문에 안쪽 영역에 존재하는 수직선 세그먼트(vertical line segment) 특징을 랜드마크로 선택한다. 그러나 선택된 특징에서는 로봇의 이동과 관측이 오차에 의해 불확실성(uncertainty)이 포함되어 있기 때문에 추정해야만 한다. 이를 위해 영역기반 스테레오 정합과 특징기반 스테레오 정합법을 이용하여 정합된 특징을 선택하고 확장 칼만필터(Extended Kalman Filter)를 이용여 선택된 특징의 위치, 길이를 추정하여 랜드마크로써 등록한다. 실내 이동환경에서의 실험을 통해 제안된 수법의 유용성을 보인다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 춘계학술발표대회
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• pp.354-357
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• 2021

Infants communicate their feelings and needs to the outside world through non-verbal methods such as crying and displaying diverse facial expressions. However, inexperienced parents tend to decode these non-verbal messages incorrectly and take inappropriate actions, which might affect the bonding they build with their babies and the cognitive development of the newborns. In this paper, we propose an aural-visual two-stream based infant cry recognition system to help parents comprehend the feelings and needs of crying babies. The proposed system first extracts the features from the pre-processed audio and video data by using the VGGish model and 3D-CNN model respectively, fuses the extracted features using a fully connected layer, and finally applies a SoftMax function to classify the fused features and recognize the corresponding type of cry. The experimental results show that the proposed system classification exceeds 0.92 in F1-score, which is 0.08 and 0.10 higher than the single-stream aural model and single-stream visual model.

• 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.

• International Journal of Contents
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• 제11권3호
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• pp.47-53
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• 2015

Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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• pp.510-514
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• 2009

이 프로그램은 Visual C++로 개발되었으며, 윈도우 운영체제내에서 파일 및 디렉토리 보안 기능을 가지고 있다. 파일 및 디렉토리 보안은 암호화/복호화 작업으로 이루어지며 파일 보안은 키 값과 라운드수를 알아야 하고, 디렉토리 보안은 비밀번호를 알아야만 복호화 할 수 있도록 설계되었다. 또한 ECB, CBC 연산방식과 3DES, SEED 알고리즘방식을 지원하며, 암호화 시 .de0 이라는 실행할 수 없는 확장자의 파일로 만들어지면서 이중보안을 할 수 있도록 개발되었다.