• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.10
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• pp.1701-1716
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• 2010

This is a follow-up study of "A study on the color image of baby's wear brands". This study was performed to classify the style images and analyze the style and color images of 7 baby wear brands that suggests how their harmony and consistency identify their clothing images. In order to classify the style image, questionnaires were organized with 40 pieces of the style board of 7 brands and 20 baby wear images adjectives. The total 324 copies were used to survey students who majored in fashion design. Questionnaires were analyzed by factor analysis from the SPSS 12.0 package program. The results of this study are as follows: First, the style image of baby wear brands was classified by 4 factors, 'loveliness', 'chic', 'liveliness', and 'pureness'. This was similar with the results of the color images that were surveyed in advance of this study. There were different characteristics for the style image of 7 baby wear brands. Second, gender (boy, girl, and new-borns) affected the style image and not season. Third, the harmony and consistency of the style and color image of 7 baby wear brands were different. It was possible to identify the clothing image of 5 baby wear brands by consistency and harmony in style and color images. However, it was evaluated that 2 baby wear brands were needed to plan the style and color image closely as well as harmoniously to make their clothing image definitive.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.187-193
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• 2012

An image authentication scheme for gray scale image through embedding a digital watermark by quantization of Integer Wavelet Transform (IWT) coefficients of the image is proposed in this paper. Proposed method is designed to detect modification of an image and to identify tampered location of the image. To embed the watermark mid-frequency band of a second level IWT was used. An approximation of the original image based on LL band was stored in LSB bits of the pixel data as a recovery mark for restoration of the image. Watermarked image has achieved a good PSNR of 40 dB compared to original cover image. Restored image quality was also very good with a PSNR of more than 35 dB compared to unmodified watermarked image even when 25% of the received image is cropped. Thus, the proposed method ensures a proper balance between the fidelity of the watermarked image and the quality of the restored image.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.639-650
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• 2014

The purpose of this study is to identify attitudes of police science students toward police image by Q-Methodology. Q-Methodology provides a method of identifying the subjectivity of each item. A survey was carried out among 40 police science students to classify the 40 selected Q-statements into a normal distribution using a 11 point scale. The collected data was analyzed by QUANL program and principal component analysis was used to identify the types of police image. As a result of this study, the police image was classified into 3 types. Type 1 can be categorized by 'fantastic image', Type 2 can be classified by 'stressful image', and Type 3 can be categorized by 'charismatic image'. These results will be used to develop a programs for improving police science students' education and will be a basis for reforming police image.

• Journal of Biomedical Engineering Research
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• v.30 no.3
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• pp.191-198
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• 2009

Phlegm smear testing for acid-fast bacilli (AFB) requires careful examination of tubercle bacilli under a microscope to distinguish between positive and negative findings. The biggest weakness of this method is the visual limitations of the examiners. It is also time-consuming, and mistakes may easily occur. This paper proposes a method of identifying tubercle bacilli that uses a computer instead of a human. To address the challenges of AFB testing, this study designs and investigates image systems that can be used to identify tubercle bacilli. The proposed system uses an electronic microscope to capture digital images that are then processed through feature extraction, image segmentation, image recognition, and neural networks to analyze tubercle bacilli. The proposed system can detect the amount of tubercle bacilli and find their locations. This paper analyzes 184 tubercle bacilli images. Fifty images are used to train the artificial neural network, and the rest are used for testing. The proposed system has a 95.6% successful identification rate, and only takes 0.8 seconds to identify an image.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.117-128
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• 2011

In this paper, we present a novel approach for contents-based medication image retrieval from a medication image database using the shape classification and color information of the medication. One major problem in developing a contents-based drug image retrieval system is there are too many similar images in shape and color and it makes difficult to identify any specific medication by a single feature of the drug image. To resolve such difficulty in identifying images, we propose a hybrid approach to retrieve a medication image based on shape and color features of the medication. In the first phase of the proposed method we classify the medications by shape of the images. In the second phase, we identify them by color matching between a query image and preclassified images in the first phase. For the shape classification, the shape signature, which is unique shape descriptor of the medication, is extracted from the boundary of the medication. Once images are classified by the shape signature, Hue and Saturation(HS) color model is used to retrieve a most similarly matched medication image from the classified database images with the query image. The proposed system is designed and developed especially for specific population- seniors to browse medication images by using visual information of the medication in a feasible fashion. The experiment shows the proposed automatic image retrieval system is reliable and convenient to identify the medication images.

• Journal of the Korean Society of Safety
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• v.9 no.1
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• pp.31-39
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• 1994

In this study, image processing were performed to recognize the shape of objects and find its center coordinate and direction to grisp the objects by the robot automatically. The proposed methods could be applied to objects even if light is reflected, and to identify the insides and outsides of objects by using the photo sensor and the difference of surface conditions. Also image segmentation is performed to the objects close to each other. These image processing methods will be increased the safety of operators by the automation of dangerous and hazardous machine works.

• Journal of Biosystems Engineering
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• v.26 no.3
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• pp.253-262
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• 2001

This study was conducted to develop the vision system of a robotic transplanter for plug-seedling. A color image processing algorithm was developed to identify and locate empty cells and bad plants in the seedling tray. The image of pepper and tomato seedling tray was segmented into regions of plants, frame and soil using threshold technique which utilized Q of YIQ for finding leaves and H of HSI for finding frame of tray in the color coordinate system. The recognition system was able to successfully identify empty cells and bad seeding and locate their two-dimensional locations. The overall success rate of the recognition system was about 99%.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.493-497
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• 2000

Fragile watermarking is a technique far autoentication/integrity of digital data. Unlike robust watermarking, il has to design to be vulnerable against some slight processing to verify the modification of digital data. Feature of fragile watermarking is to identify the modifications of data and to locate some places modification occurred at the same time, so it has to identify slight changes of small range if possible. In this paper, fragile watermarking is proposed that the changes of small range on image can be identified using the watermark sequence with period and the values of low bit planes in an image.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.600-606
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• 2018

Smart city is currently the main direction of development. The automatic management of instrumentation is one task of the smart city. Because there are a lot of old instrumentation in the city that cannot be replaced promptly, how to makes low-cost transformation with Internet of Thing (IoT) becomes a problem. This article gives a low-cost method that can identify code wheel instrument information. This method can effectively identify the information of image as the digital information. Because this method does not require a lot of memory or complicated calculation, it can be deployed on a cheap microcontroller unit (MCU) with low read-only memory (ROM). At the end of this article, test result is given. Using this method to modify the old instrumentation can achieve the automatic management of instrumentation and can help build a smart city.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.583-594
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• 2021

In this paper, we propose wavelet-based procedures to identify the difference between images, including portraits and handwriting. The proposed methods are based on a novel combination of multiscale methods with a regularization technique. The multiscale method extracts the local characteristics of an image, and the distinct features are obtained through the regularized regression of the local characteristics. The regularized regression approach copes with the high-dimensional problem to build the relation between the local characteristics. Lytle and Yang (2006) introduced the detection method of forged handwriting via wavelets and summary statistics. We expand the scope of their method to the general image and significantly improve the results. We demonstrate the promising empirical evidence of the proposed method through various experiments.