• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.251-256
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• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.

• Journal of Industrial Convergence
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• v.20 no.4
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• pp.71-77
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• 2022

It is a reality that office workers in modern society cannot overlook their appearance management for promotion in the workplace that does not fall behind in competition with others and smooth human relationships. According to this social trend, it is time to conduct an in-depth cosmetology study on the appearance management and perception of office workers, including hair styles. Therefore, this study analyzed the hair style type and preference closely by cross-analyzing the differences between groups by classifying the occupational persons of female airline crew, female soldiers, female sportsmen, female lawyers, and female nurses into age, marriage, academic background, and occupation. As result of study, it was found that different women in each occupational group had different results, such as their current hair style type and hair texture, the use of current hair styling products, and their personal preference for women's hairstyles and hair colors. This study will be used as basic data for developing new mode items that meet customer needs in the beauty marketing market and researching customer demand.

• Spatial Information Research
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• v.21 no.3
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• pp.11-19
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• 2013

Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.173-180
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• 2014

Compressive sensing is a new signal acquisition paradigm that enables sparse/compressible signal to be sampled under the Nyquist-rate. To fully benefit from its much simplified acquisition process, huge efforts have been made on improving the performance of compressive sensing recovery. However, concerning color images, compressive sensing recovery lacks in addressing image characteristics like energy distribution or human visual system. In order to overcome the problem, this paper proposes a new group-sparsity hard thresholding process by preserving some RGB-grouped coefficients important in both terms of energy and perceptual sensitivity. Moreover, a smoothed group-sparsity iterative hard thresholding algorithm for compressive sensing of color images is proposed by incorporating a frame-based filter with group-sparsity hard thresholding process. In this way, our proposed method not only pursues sparsity of image in transform domain but also pursues smoothness of image in spatial domain. Experimental results show average PSNR gains up to 2.7dB over the state-of-the-art group-sparsity smoothed recovery method.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.2
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• pp.1-12
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• 2023

In the current era of the global mobile smart device revolution, electronic devices are required in all spaces that people interact with. The establishment of the internet of things (IoT) among smart devices has been recognized as a crucial objective to advance towards creating a comfortable and sustainable future society. In-mold electronic (IME) processes have gained significant industrial significance due to their ability to utilize conventional high-volume methods, which involve printing functional inks on 2D substrates, thermoforming them into 3D shapes, and injection-molded, manufacturing low-cost, lightweight, and functional components or devices. In this article, we provide an overview of IME and its latest advances in application. We review biomimetic nanomaterials for constructing self-supporting biosensor electronic materials on the body, energy storage devices, self-powered devices, and bio-monitoring technology from the perspective of in-mold electronic devices. We anticipate that IME device technology will play a critical role in establishing a human-machine interface (HMI) by converging with the rapidly growing flexible printed electronics technology, which is an integral component of the fourth industrial revolution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.382-389
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• 2019

A novel folding process is proposed using a repeated cold-die forging and annealing to form a sterling silver ring. Sterling silver plate was cut into a doughnut shape, and lattices with 0.43-mm line-width were imprinted on it. The sample was folded by forging using dies with slopes of $45^{\circ}$, $60^{\circ}$, and $75^{\circ}$ and annealing. For comparison, samples were also fabricated without annealing. Strain was identified by measuring the length of lattices. Vernier calipers, a Vickers hardness tester, an optical microscope, and a UV-VIS colorimeter were used to determine the size, hardness, microstructure, and body color. Without annealing, cracks occurred. However, successful deformation was possible when annealing was used. The results of macro strain measurements show that the outer diameter and width decreased, while the inner diameter and thickness increased after the final process. The maximum strain was increased 0.128 toward the parallel direction. The Vickers hardness decreased after annealing and increased after the folding process. The microstructure results showed that the grain size increased after annealing but decreased after folding. The color difference based on the Lab index was under 10 for all processes. Eventually, a doughnut-shaped silver plate was successfully deformed into a ring shape by the folding process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.84-90
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• 2020

As the uploading and downloading of data through the Internet is becoming more common, data including personal information are easily exposed to unauthorized users. In this study, we detect a target area in images that contain personal information, except for the background, and we protect the detected target area by using a blocking method suitable for the surrounding situation. In this method, only the target area from color image input containing personal information is segmented based on skin color. Subsequently, blurring of the corresponding area is performed in multiple stages based on the surrounding situation to effectively block the detected area, thereby protecting the personal information from being exposed. Experimental results show that the proposed method blocks the object region containing personal information 2.3% more accurately than an existing method. The proposed method is expected to be utilized in fields related to image processing, such as video security, target surveillance, and object covering.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.23-30
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• 2010

It is important for the strategy of cosmetic sales to investigate the sensibility and the preference degree in the environment that the makeup style has been changed focusing on the consumer center. We proposed the human sensibility ergonomics makeup recommendation system (MakeupRS) using the context sensor information applying the collaborative filtering technique as one of methods in the makeup style development centered on the consumer's sensibility and the preference. In the collaborative filtering technique, the Pearson correlation coefficient applying to the case amplification is used to calculate similarity weights between the users. To investigate the sensibility according to the effect of makeup styles, the makeup styles were analyzed in terms of 6 style factors, such as, the foundation, the color lens, the eye shadow, the eye lash, the cheek brusher, and the lipstick. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the human sensibility ergonomics makeup recommendation system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.277-280
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• 2016

Real-time remote monitoring system has an important value in many surveillance situations. It allows someone to be informed of what is happening in his monitoring locations. Kinect v2 is a new kind of camera which gives computers eyes and can generate different data such as color and depth images, audio input and skeletal data. In this paper, using Kinect v2 sensor with its depth image, we present a monitoring system in a space covered by Kinect. Therefore, based on space covered by Kinect camera, we define a target area to monitor using depth range by setting minimum and maximum distances. With computer vision library (Emgu CV), if there is an object tracked in the target space, kinect camera captures the whole image color and sends it in database and user gets at the same time a notification on his mobile device wherever he is with internet access.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.389-392
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• 2010

In this paper, it presents to detect location using structural information of hand from the input color images on Webcam and to recognize hand gestures. In this system, based on the skin color, the image changes a binary number and labels. Within each labeled area, we can find the Maximum Inscribed Circle using Voronoi Diagram. This circle can find the center of hand. And the circle extracts hand region from analyzing the ellipse elements to relate Maximum Inscribed Circle. We use the Maximum Inscribed Circle and the ellipse elements as characteristic of hand gesture recognition. In various environments, we cannot recognize the object that have similar colors like the background colors. But the proposed algorithm has the advantage that can be effectively eliminated about it.