• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.277-283
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• 2021

This paper addresses the problem of vision-based mask filter inspection for mask production systems. Machine learning-based approaches can be considered to solve the problem, but they may not be applicable to mask filter inspection if normal and anomaly mask filter data are not sufficient. In such cases, handcrafted image processing methods have to be considered to solve the problem. In this paper, we propose a hierarchical correlation-based approach that combines handcrafted image processing methods to detect anomaly mask filters. The proposed approach combines image rotation, cropping and resizing, edge detection of mask filter parts, average blurring, and correlation-based decision. The proposed approach was tested and analyzed with real mask filters. The results showed that the proposed approach was able to successfully detect anomalies in mask filters.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.9
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• pp.46-58
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• 1993

Owing to the nature of locality in mask layouts, it appears that most mask layout problems can be solved by transforming a part of the given mask layout into a better layout segment continuously toward a global suboptimal solution. This notion of local transformation addresses major weak points of existing mask layout processing systems, which lack both extensibility and unifiability. This paper attempts to elaborate upon developing a new rule-based mask layout transformation system wherein most of the mask layout problems can be solved under the unified framework of local mask layout transformation. The rule-based mask layout transformation system is applicable to various mask layout problems such as net extraction, mask layout compaction, mask layout editing, and design rule checking. The experimental results show that the rule-based expert system approach is an efficient means of solving those mask layout problems, and thus confronting major drawbacks of existing layout processing systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.268-271
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• 2005

Etch resistance of mask layer on silicon substrate modified by AFM-based Tribo-Nanolithography (TNL) in Aqueous Solution in an aqueous solution was demonstrated. n consists or sequential processes, nano-scratching and wet chemical etching. The simple scratching can form a mask layer on the silicon substrate, which acting as an etching mask. For TNL, a specially designed cantilever with diamond tip, allowing the formation of mask layer on silicon substrate easily by a simple scratching process, has been applied instead of conventional silicon cantilever fur scanning. This study demonstrates how the TNL parameters can affect the etch resistance of mask layer, hence introducing a new process of AFM-based maskless nanolithography in aqueous solution.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.337-346
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• 2022

This paper addresses the problem of vision-based ear loops ansd attachment inspection in mask production lines. This paper focuses on connections with ear loops and mask filter by an efficient combined approach. The proposed method used a template matching, shape detection and summation of histogram with preprocessing. We had a parameter for detecting defects heuristically. If the shape vertices are lower than the parameters our proposed method will find defective mask automatically. After finding normal masks in mask ear loops attachment status inspection algorithm our proposed method conducts attachment amount inspection. Our experimental results showed that the precision is 1 and the recall is 0.99 in the mask attachment status inspection and attachment amount inspection.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.65-73
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• 2017

This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.159-166
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• 2021

COVID-19 has dramatically changed people's daily life. Wearing masks is considered as a simple but effective way to defend the spread of the epidemic. Hence, a real-time and accurate mask wearing detection system is important. In this paper, a deep learning-based mask wearing detection system is developed to help people defend against the terrible epidemic. The system consists of three important functions, which are image detection, video detection and real-time detection. To keep a high detection rate, a deep learning-based method is adopted to detect masks. Unfortunately, according to the suddenness of the epidemic, the mask wearing dataset is scarce, so a mask wearing dataset is collected in this paper. Besides, to reduce the computational cost and runtime, a simple online and real-time tracking method is adopted to achieve video detection and monitoring. Furthermore, a function is implemented to call the camera to real-time achieve mask wearing detection. The sufficient results have shown that the developed system can perform well in the mask wearing detection task. The precision, recall, mAP and F1 can achieve 86.6%, 96.7%, 96.2% and 91.4%, respectively.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.476-481
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• 2023

Objective : The latest version of the Leksell Gamma Knife Icon^TM allows for mask- and frame-based fixation. Although mask fixation provides fractionated treatment and immobilization using a noninvasive method, it is not free from collision. The authors investigated the collision problem with a modified mask fixation method. Methods : This study presents a case of two meningiomas in the frontal area, where a collision occurs in the occipital area. A modified mask fixation method was introduced to avoid the collision : first, the edges of the head cushion were cut off and polystyrene beads with a diameter of approximately 5 cm were removed. Next, the head cushion was sealed using a stapler. Finally, the head cushion was flattened in the adapter. We compared the shot coordinates, 3-dimensional (3D) error, clearance distance, and vertical depth of the head cushion between the initial and modified mask fixations. Results : When comparing the initial and modified mask fixations, the difference in the shot coordinates was +10.5 mm along the y-axis, the difference in the 3D error was approximately 18 mm, and the difference in clearance was -10.2 mm. The head cushion was approximately 8 mm deeper in the modified mask fixation. Conclusion : Based on these findings, we recommend a modified mask fixation method for gamma knife radiosurgery using ICON with a collision.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.381-388
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• 2022

In instance segmentation, Mask-RCNN is mostly used as a base model. Increasing the performance of Mask-RCNN is meaningful because it affects the performance of the derived model. Mask-RCNN has a transform module for unifying size of input images. In this paper, to improve the Mask-RCNN, we apply deep-learning-based ASSR to the resizing part in the transform module and inject calculated scale information into the model using IM(Integration Module). The proposed IM improves instance segmentation performance by 2.5 AP higher than Mask-RCNN in the COCO dataset, and in the periment for optimizing the IM location, the best performance was shown when it was located in the 'Top' before FPN and backbone were combined. Therefore, the proposed method can improve the performance of models using Mask-RCNN as a base model.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1213-1218
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• 2018

Recently introduced Mask R - CNN presents a conceptually simple, flexible, general framework for instance segmentation of objects. In this paper, we propose an algorithm for efficiently searching objects of images, while creating a segmentation mask of heat generation part for an instance which is a heating element in a heat sensed image acquired from a thermal infrared camera. This method called a mask R - CNN is an algorithm that extends Faster R - CNN by adding a branch for predicting an object mask in parallel with an existing branch for recognition of a bounding box. The mask R - CNN is added to the high - speed R - CNN which training is easy and fast to execute. Also, it is easy to generalize the mask R - CNN to other tasks. In this research, we propose an infrared image detection algorithm based on R - CNN and detect heating elements which can not be distinguished by RGB images. As a result of the experiment, a heat-generating object which can not be discriminated from Mask R-CNN was detected normally.

• Science of Emotion and Sensibility
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• v.7 no.2
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• pp.123-131
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• 2004

This study has an aim to find out sensible factors of hahae Mask and to be helpful in developing design of products related with cultural products. This study selected and analyzed 32 vocabularies about sensible adjective to evaluate image of hahae Mask. Firstly, this study investigated image of hahae Mask through 32 vocabularies about sensible adjective and categorized 5 factors including 'attractive', 'native', 'interesting', 'active', and 'elaborate'. Secondly, sense had significant differences in 'native' and, 'interesting' based on kinds. Especially yangban Mask has more powerful nativeness than choraengi Mask, and is more interesting than jung Mask, baekjeong Mask, and bune Mask. Thirdly, the materials used in the products of hahae Mask generated differences of sensibility in elaborateness. Especially, elaborate image was emphasized about materials of glass. Fourthly, sensible image of hahae Mask was dependent upon population-statistic characteristics (age, sex, education) and characteristics of products(materials, kinds of Mask). If development of cultural products related with hahae Mask considers five sensible factors based on this study, it will contribute to development of design which coincides with consumers' needs.