• International Journal of Control, Automation, and Systems
• /
• v.1 no.4
• /
• pp.511-514
• /
• 2003

The Infrared Camera usually detects only Infrared waves emitted from the light in order to illustrate the temperature distribution. An Infrared diagnosis system can be applied to various fields. But the defect discrimination can be automatic or mechanized in the special shoes total inspection system. This study introduces a method for special shoes nondestructive total inspection. Performance of the proposed method is shown through thermo-Image.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.9
• /
• pp.1340-1347
• /
• 1989

For the efficient recognition of Korean Alphabets, a tree structure discrimination algorithm employing NRF-SDF concept is proposed. This algorithm consists of several main-steps, which contain several sub-steps. Each step contains vowels or consonants for training image. This algorithm reduces processing and recognition time than any other conventional algorithms for recognition of Korean Alphabets. A simulation results indicated that this algorithm has a satisfactory performance.

• The Journal of the Acoustical Society of Korea
• /
• v.12 no.2
• /
• pp.51-59
• /
• 1993

본 논문에서는 입력으로 들어 온 레인지데이타에서 특징 추출을 통하여 3차원물체를 식별하는 방법을 제안하고자 한다. Z축 기울기를 이용하여 형상특징을 추출하고, 각 표면조각에서 법선벡터를 구해 기하학적 특징을 추출한다. 그 후 위에서 구한 특징들을 퍼지화데이타로 만들어 일치도 연산에 의해 표준 물체와 입력화상 물체 사이의 정합을 수행한다. 최종적으로 본 논문의 유용성을 실험에 의해 입증하고자 한다.

• Proceedings of the KOSOMBE Conference
• /
• v.1991 no.05
• /
• pp.18-21
• /
• 1991

In this paper, the effect of background grey levels on the visual perception of target image displayed on CRT monitor has been investigated. The purpose of this study is to investigate the efficacy of CRT monitor as a display medium of image information especially in medical imaging field. Three sets of experiments have been performed in this study; the first was to measure the luminance response of CRT monitor and to find the best fitting equation, and the second was the psychophysical experiment measuring the threshold grey level difference between the target image and the background required for visual discrimination for various background grey levels, and the third was to develop a visual model that is predictable of the threshold grey level difference measured in the psychophysical experiment. The result of psycophysical experiment shows that the visual perception performance is significantly degraded in the range of grey levels lower than 50, which is turned out due to the low luminance change of CRT monitor in this range while human eye has been adapted to relatively bright ambient illumination.

• Journal of Biomedical Engineering Research
• /
• v.14 no.1
• /
• pp.63-72
• /
• 1993

In this paper, the effect of background grey levels on the visual perception of target image displayed on CRT monitor has been investigated. The purpose of this study is to investigate the efficacy of CRT monitor as a display medium of image Information especially in medical imaging field. Tllree sets of experiments have been performed in this study : the first was to measure the luminance response of CRT monitor and to find the best fitting equation, and the second was the psychophysical experiment measuring the threshold grey level differences between the target image and the background required for visual discrimination (or various background grey levels, and the third was to develop a visual model that is predictable of the threshold grey level difference measured in the psychophysical experiment. The result of psycophysical experiment shows that the visual perception performance is significantly degraded in the range of grey levels lower than 50, which is turned out due to she low luminance change of CRT monitor in this range while human eye has been adapted lo relatively bright ambient illumination. And it Is also shown in the simulation study using the developed visual model that the dominant factor degrading the visual performance is the reflected light from the monitor surface by ambient light in general illumination condition.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.3
• /
• pp.522-538
• /
• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• Fashion & Textile Research Journal
• /
• v.8 no.1
• /
• pp.113-122
• /
• 2006

The purpose of the study was to identify the motives of women's appearance-management behavior, and examine how women perceived the appearance -management behavior and pursuit of ideal body image. The depth interview method was managed to five female subjects who had experiences in plastic surgery and obesity treatment. The instance analysis used in this study. The results were as follows : There were four types of women's appearance-management behavior. First, women perceived themselves by using other people's evaluation, and it was the first motive of appearance-management behavior. It shows that appearance is not based on the real self-image but is the evaluated self-image by others. Second, women were willing to suffer the pain in the plastic surgery and obesity treatment by the expectation of appearance improvement. It means the result of reducing the difference between the actual self-figure and the ideal self-image. Third, the sexual discrimination culture had an influence on appearance-management behavior. It seems the sense of male superiority spreaded over the Korean society. Lastly, women improved self-satisfaction and self-esteem through their physical appearance as an alternative method for better life.

• Journal of the Semiconductor & Display Technology
• /
• v.7 no.1
• /
• pp.11-16
• /
• 2008

Confocal scanning microscopy is a widely used technique for three dimensional measurements because it is characterized by high resolution, high SNR and depth discrimination. Generally an image is generated by moving one optical probe that satisfies the confocal condition on the specimen. Measurement speed is limited by movement speed of the optical probe; scanning speed. To improve measurement speed we increase the number of optical probes. Specimen region to scan is divided by optical probes. Multi-point information each optical probe points to can be obtained simultaneously. Therefore image acquisition speed is increased in proportion to the number of optical probes. And multiple optical probes from red, green and blue laser sources can be used for color imaging and image quality, i.e., contrast, is improved by adding color information by this way. To conclude, this technique contributes to the improvement of measurement speed and image quality.

• Korean Journal of Remote Sensing
• /
• v.35 no.4
• /
• pp.535-544
• /
• 2019

This study demonstrated the ability of a Landsat-8 OLI multispectral data to identify and delineate hydrothermal alteration zones around auriferous prospects within the crystalline basement, North-western Nigeria. Remote sensing techniques have been widely used in lithological, structural discrimination and alteration rock delineation, and in general geological studies. Several artisanal mining activities for gold deposit occur in the surrounding areas within the basement complex and the search for new possible mineralized zones have heightened in recent times. Systematic Landsat-8 OLI data processing methods such as colour composite, band ratio and minimum noise fraction were used in this study. Colour composite of band 4, 3 and 2 was displayed in Red-Green-Blue colour image to distinguish lithologies. Band ratio ${\frac{4}{2}}$ image displayed in red was used to highlight ferric-ion bearing minerals(hematite, goethite, jarosite) associated with hydrothermal alteration, band ratio ${\frac{5}{6}}$ image displayed in green was used to highlight ferrous-ion bearing minerals such as olivine, amphibole and pyroxenes, while ratio ${\frac{6}{7}}$ image displayed in blue was used to highlight clay minerals, micas, talc-carbonates, etc. Band rationing helped to reduce the topographic illumination effect within images. The result of this study showed the distribution of the lithological units and the hydrothermal alteration zone which can be further prospected for mineral reserves.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.11
• /
• pp.4426-4442
• /
• 2020

Since scene segmentation is becoming a hot topic in the field of autonomous driving and medical image analysis, researchers are actively trying new methods to improve segmentation accuracy. At present, the main issues in image semantic segmentation are intra-class inconsistency and inter-class indistinction. From our analysis, the lack of global information as well as macroscopic discrimination on the object are the two main reasons. In this paper, we propose a Densely connected residual Attention network (DA-Res2Net) which consists of a dense residual network and channel attention guidance module to deal with these problems and improve the accuracy of image segmentation. Specifically, in order to make the extracted features equipped with stronger multi-scale characteristics, a densely connected residual network is proposed as a feature extractor. Furthermore, to improve the representativeness of each channel feature, we design a Channel-Attention-Guide module to make the model focusing on the high-level semantic features and low-level location features simultaneously. Experimental results show that the method achieves significant performance on various datasets. Compared to other state-of-the-art methods, the proposed method reaches the mean IOU accuracy of 83.2% on PASCAL VOC 2012 and 79.7% on Cityscapes dataset, respectively.