• Journal of Korean Society for Atmospheric Environment
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• v.19 no.1
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• pp.67-76
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• 2003

Recently consideration of health and interest on bio aerosols have been growing steadily. In this study, inertial impactor, which can be used to collect airborne particles and bio aerosols, was newly devised for real-time observation on the particles collected on impaction plate. and named Visual Impactor. Flow field and particle trajectory in the space between nozzle and impaction plate was analyzed numerically, and the collection effciencies were calculated. Calibration and performance evaluation of the Visual Impactor was conducted with polydisperse aerosols generated from 0.1％ sodium chloride solution. Cut-off diameter from numerical simulation was in good agreement with that from experimental results. Because of particle bounce and particle deposition on nozzle tip due to short jet-to-plate distance, the collection efficiencies from numerical and experimental analyses were different slightly. Visual Impactor was used to collect airborne particles, and the features of collected particles could be seen in real-time. Airborne particles in different weather conditions (fine, cloudy, and rainy) were sampled and compared one another The features of collected airborne particles were dependent strongly upon relative humidity. In addition, with hours elapsing, shapes and colors of collected particles were changed by evaporation and surface tension, etc.

• Journal of Korean Neurosurgical Society
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• v.29 no.6
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• pp.815-821
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• 2000

Parasplenial arteriovenous malformations(AVMs) are rare vascular malformations which have distinct clinical and anatomical features. They are situated at the confluence of the hippocampus, isthmus of the cingulate gyrus and the gyrus occipitotemporalis medialis. These lesions are anterior to the calcarine sulcus and their apex extends towards the medial surface of the trigonum. Posterolaterally, these lesions are in close proximity to the visual cortex and optic radiation. The objectives in the surgery of parasplenial AVMs are complete resection of the lesions and preservation of vision. These objectives must be achieved with comprehensive understanding of the following anatomical features :1) the deep central location of the lesions within eloquent brain tissue ; 2) the lack of cortical representation of the AVMs that requires retraction of visual cortex ; 3) deep arterial supply ; 4) deep venous drainage ; 5) juxtaposition to the choroid plexus with which arterial supply and venous drainage are shared. A 16-year-old female student presented with intraventricular hemorrhage from a right parasplenial-subtrigonal AVM. The lesion, fed by posterior cerebral artery and drained into the vein of Galen, was successfully treated by the inter-hemispheric parietooccipital approach. To avoid visual field defect a small incision was made on precuneus anterior to the calcarine sulcus. In this report, the authors describe a surgical approach with special consideration on preservation of visual field.

• The Research Journal of the Costume Culture
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• v.18 no.6
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• pp.1318-1330
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• 2010

The 21st century is the age when a sensational image has more explanatory power and can deliver a more powerful message than a message consisting of logical thinking. Powerful visual images create a big impact on many people throughout the world, overcoming linguistic barriers and even replacing language as a means of communication. In the fashion field, the concept and power of visual images within the new multimedia of the 21st century are becoming increasingly important. In recent years, other than the above methods, videos, movies and animation features have been produced directly to enhance visual effects and attempts are increasing to use these new tools as communication methods. This study focuses on animation contents that have been used in the fashion industry to overcome prejudice of luxury international brands that feature images that emphasize value, quality and heritage. The purpose of this study is to focus on the specific character of fashion animation in order to overview the concept of 21st video fashion communication and to show how the collection concept that includes color and detail places an emphasis on visual images. Analysis of previous research, theoretical research through literature and case study on Prada fashion animation led to the following conclusion. The common features of two different Prada fashion animation show that both animation have the following features in common : realism, dramatic impact and convergence for expression methods, and creativeness, hybrid and a happy ending for contents. Beginning with this study, I believe that various angles of interest and concern about communication in the fashion world, which is a social and cultural phenomenon that changes rapidly, can be will be looked at and learned from.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.325-335
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• 1996

Visual features are crucial for monitoring the growth state, indexing the drying performance, and grading the quality of oak mushrooms. A computer vision system with neural net information processing technique was utilized to quantize quality factors of a dried oak mushrooms distributed over the cap and gill sides. In this paper, visual feature extraction algorithm were integrated with the neural net processing to deal with various fuzzy patterns of mushroom shapes and to compensate the fault sensitiveness of the crisp criteria and heuristic rules derived from the image processing results. The proposed algorithm improved the segmentation of the skin features of each side, the identification of cap and gill surfaces, the identification of stipe states and removal of the stipe, etc. And the visual characteristics of dried oak mushrooms were analyzed and primary visual features essential to tile quality evaluation were extracted and quantized. In this study, black and white gray images were captured and used for the algorithm development.

• Journal of Bio-Environment Control
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• v.1 no.1
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• pp.37-51
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• 1992

Quantizing and extracting visual features of mushroom(Lentinus edodes L.) are crucial to the sorting and grading automation, the growth state measurement, and the dried performance indexing. A computer image processing system was utilized for the extraction and measurement of visual features of front and back sides of the mushroom. The image processing system is composed of the IBM PC compatible 386DK, ITEX PCVISION Plus frame grabber, B/W CCD camera, VGA color graphic monitor, and image output RGB monitor. In this paper, an automatic thresholding algorithm was developed to yield the segmented binary image representing skin states of the front and back sides. An eight directional Freeman's chain coding was modified to solve the edge disconnectivity by gradually expanding the mask size of 3$\times$3 to 9$\times$9. A real scaled geometric quantity of the object was directly extracted from the 8-directional chain element. The external shape of the mushroom was analyzed and converted to the quantitative feature patterns. Efficient algorithms for the extraction of the selected feature patterns and the recognition of the front and back side were developed. The developed algorithms were coded in a menu driven way using MS_C language Ver.6.0, PC VISION PLUS library fuctions, and VGA graphic functions.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.32-41
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• 1990

This paper proposes a method of using image features in serving a robot manipulator. Specifically, the con-cept 'feature' is first mathematically defined and then differential relationship between the robot motion and feature vector is derived in terms of Feature Jacobian Matrix and its generalized inverse. Also, by using more features than the number of DOFs of the robot, the visual servoing performance is shown to be improv-ed. Via various examples, the method of feature-based servoing of a robot proposed in this paper is proved to be effective for conducting object-oriented robotic tasks.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.995-1000
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• 1999

This paper presents a optic system and a visual inspection algorithm looking for solder joint defects of J-lead chip which are more integrate and smaller than ones with Gull-wing on PCBs(Printed Circuit Boards). The visual inspection system is composed of three sections : host PC, imaging and driving parts. The host PC part controls the inspection devices and executes the inspection algorithm. The imaging part acquires and processes image data. And the driving part controls XY-table for automatic inspection. In this paper, the most important five features are extracted from input images to categorize four classes of solder joint defects in the case of J-lead chip and utilized to a back-propagation network for classification. Consequently, good accuracy of classification performance and effectiveness of chosen five features are examined by experiment using proposed inspection algorithm.

• International Journal of Contents
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• v.2 no.1
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• pp.22-28
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• 2006

In this paper, we propose new semantic contents modeling using individual features, associative relations and visual features for efficiently supporting browsing and retrieval of video semantic contents. And we implement and design a browsing and retrieval system based on the semantic contents modeling. The browsing system supports annotation based information, keyframe based visual information, associative relations, and text based semantic information using a tree based browsing technique. The retrieval system supports text based retrieval, visual feature and associative relations according to the retrieval types of semantic contents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.667-673
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• 2006

In this paper, we present a visual inspection system for a CoG using statistical features. After rotational error of an input image is compensated using Hough transformation, an inspection area is obtained by using projection method. Then the final result is derived from statistical features of segmented pad areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.451-465
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• 2017

This paper presents a novel discriminative visual tracking algorithm with an adaptive incremental extreme learning machine. The parameters for an adaptive incremental extreme learning machine are initialized at the first frame with a target that is manually assigned. At each frame, the training samples are collected and random Haar-like features are extracted. The proposed tracker updates the overall output weights for each frame, and the updated tracker is used to estimate the new location of the target in the next frame. The adaptive learning rate for the update of the overall output weights is estimated by using the confidence of the predicted target location at the current frame. Our experimental results indicate that the proposed tracker can manage various difficulties and can achieve better performance than other state-of-the-art trackers.