• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.108-112
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• 2023

Precision manufacturing technology is rapidly developing due to the extreme miniaturization of semiconductor processes to comply with Moore's Law. Accurate and precise alignment, which is one of the key elements of the semiconductor pre-process and post-process, is very important in the semiconductor process. The center detection of wafer align marks plays a key role in improving yield by reducing defects and research on accurate detection methods for this is necessary. Methods for accurate alignment using traditional image sensors can cause problems due to changes in image brightness and noise. To solve this problem, engineers must go directly into the line and perform maintenance work. This paper emphasizes that the development of AI technology can provide innovative solutions in the semiconductor process as high-resolution image and image processing technology also develops. This study proposes a new wafer center detection method through variable thresholding. And this study introduces a method for detecting the center that is less sensitive to the brightness of LEDs by utilizing a high-performance object detection model such as YOLOv8 without relying on existing algorithms. Through this, we aim to enable precise wafer focus detection using artificial intelligence.

• Broadcasting and Media Magazine
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• v.5 no.1
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• pp.59-71
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• 2000

This paper presents a survey of the CMOs-based image sensor and its applications to various real field digital camera. CMOS image sensor, called active pixel sensor (APS), has many interesting properties such ash I회 sensitivity, high speed readout, random access and lower power consumption when it is compared with CCd. this paper also addresses the state-of-the-art of CMOS image sensor, and gives some examples of its application to digital camera and special-purpose cameras. with the advancement of semiconductor technology, CMOS image sensor is a future technology for imaging system, and will be widely used in the filed of image capturing for consumer electronics and scientific measurements.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.135-138
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• 2020

This paper suggests a method of automatic clustering to search of relevant digital photos using geo-coded information. The provided scheme labels photo images with their corresponding global positioning system coordinates and date/time at the moment of capture, and the labels are used as clustering metadata of the images when they are in the use of retrieval. Experimental results show that geo-location information can improve the accuracy of image retrieval, and the information embedded within the images are effective and precise on the image clustering.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.29-30
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• 2021

본 논문에서는 이미지 분류에 쓰이는 최신 모델로 CNN과 ImageNet을 기반으로 한 EfficientNet을 활용해서 Square, Oval, Oblong, Round, Heart 총 다섯 가지의 얼굴 모양으로 분류하는 task에 두 가지 데이터로 실험해보고 추가적으로 Image Augmentation 기법을 활용해 성능향상을 보였다.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.243-258
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• 2011

With increasing interest in ubiquitous computing technology, an infrastructure for the short-distance wireless communication has been extended socially, bringing spotlight to the security system using the image or location. In case of existing security system, there have been issues such as the occurrences of blind spots, difficulty in recognizing multiple objects and storing of the unspecified objects. In order to solve this issue, zone-based location-estimation search system for the image have been suggested as an alternative based on the real-time location determination technology combined with image. This paper intends to suggest the search service for the image zone-based location-estimation. For this, it proposed the location determination algorism using IEEE 802.15.4/ZigBee's RSSI and for real-time image service, the RTP/RTCP protocol was applied. In order to combine the location and image, at the event of the entry of the specified target, the record of the time for image and the time of occurrence of the event on a global time standard, it has devised a time stamp, applying XML based meta data formation method based on the media's feature data based in connection with the location based data for the events of the object. Using the proposed meta data, the service mode which can search for the image from the point in time when the entry of the specified target was proposed.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.661-672
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• 2008

In this paper an algorithm, based on extracting a certain target of an image, is proposed that is capable of performing bilevel thresholding of image with multimodal distribution. Each pixel in the image has a membership value which is used to denote the characteristic relationship between the pixel and its belonging region (i.e. the object or background). Using the membership values of image set, a new measurement, which simultaneously measures the measure of fuzziness and the conditional entropy of the image, is calculated. Then, thresholds are found by optimally minimizing calculated measurement. In addition, a fuzzy range is defined to improve the threshold values. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively extract the meaningful target from the input image. The resulting image can preserve the object region we target very well.

• Journal of Platform Technology
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• v.6 no.4
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• pp.26-33
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• 2018

In this paper, we propose an image retrieval algorithm for real-time processing and design it as hardware. The proposed method is based on the classification of BoWs(Bag of Words) algorithm and proposes an image search algorithm using bit stream. K-fold cross validation is used for the verification of the algorithm. Data is classified into seven classes, each class has seven images and a total of 49 images are tested. The test has two kinds of accuracy measurement and speed measurement. The accuracy of the image classification was 86.2% for the BoWs algorithm and 83.7% the proposed hardware-accelerated software implementation algorithm, and the BoWs algorithm was 2.5% higher. The image retrieval processing speed of BoWs is 7.89s and our algorithm is 1.55s. Our algorithm is 5.09 times faster than BoWs algorithm. The algorithm is largely divided into software and hardware parts. In the software structure, C-language is used. The Scale Invariant Feature Transform algorithm is used to extract feature points that are invariant to size and rotation from the image. Bit streams are generated from the extracted feature point. In the hardware architecture, the proposed image retrieval algorithm is written in Verilog HDL and designed and verified by FPGA and Design Compiler. The generated bit streams are stored, the clustering step is performed, and a searcher image databases or an input image databases are generated and matched. Using the proposed algorithm, we can improve convenience and satisfaction of the user in terms of speed if we search using database matching method which represents each object.

• Journal of Technologic Dentistry
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• v.33 no.4
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• pp.505-516
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• 2011

Purpose: The purpose of this study is to supply basic data to establish new image for dental technicians by reflecting onto the education of dental technicians by grasping the image of dental technicians with the subjects of students in department of dental technology. Methods: It was studied with self-filling-in method through structured questionnaire from September 26, to October 21, 2011, with 421 subjects of the students in the department of dental technology in two colleges in Daegu. SPSS 18.0 for Windows was used to analyze the data, and frequency and percentage were used for statistic analysis, and correlation analysis and Multiple Linear Regression Analysis were used with mean and SD per each question. Results: It showed the highest recognition that the dental technicians is a 'specialist' as 4.66; the dental technicians has strong responsibility in his work as 4.42; the dental technicians takes an important role in improvement of public oral health as 4.39; and the dental technicians has professional intelligence and high technique as 4.33. So, it was found that they had image of professional and important role for oral health, and had their pride and selfconfidence as future dental technicians. Meanwhile, it showed that they had negative related-image as well as a job, that the dental technicians is too busy as 4.48; it requires improvement on image in the future as 4.27; it is a hard job with too much stress as 4.13. Conclusion: It is required for us and school to have continuous change and effort to make the students in the department of dental technology have positive mind for the dental technology to make them have pride for their job.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.2
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• pp.173-184
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• 2015

This study examined the impacts of the cultural proximity of Chinese consumers on the image of both country and product, and investigated how they are related to purchase intention of Korea fashion. Subjects were Chinese female consumers in their 20s and 30s, living in Yangtze River delta and Seoul. The results of the study were as follows: 1) The cultural proximity had a significant influence on the country image and fashion product image. Chinese consumers with more emotional proximity had more positive attitude towards country image, such as politics, economics, technology, cultures and people image. And consumers who had higher interest in Korea and Korean culture evaluated the quality, design, value and reputation of Korean fashion more positively. 2) Chinese consumers with positive attitude towards people, technology and culture image seemed to prefer fashion product. Specifically, the dimensions of country image had a different influence on the fashion product image such as product quality, design, value, reputation. 3) The Korea country image and fashion product image had also affected on purchase intention of Korean fashion products. Consumers with positive attitude towards people and technology image had higher purchase intention of Korea fashion products. And consumers with positive attitude towards reputation, value and design of fashion products had higher purchase intention of fashion products.