• Journal of Sensor Science and Technology
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• v.30 no.1
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• pp.15-19
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• 2021

Image processing is one of the major techniques that are used for computer vision. Nowadays, researchers are using machine learning and deep learning for the aforementioned task. In recent years, digit recognition tasks, i.e., automatic meter recognition approach using electric or water meters, have been studied several times. However, two major issues arise when we talk about previous studies: first, the use of the deep learning technique, which includes a large number of parameters that increase the computational cost and consume more power; and second, recent studies are limited to the detection of digits and not storing or providing detected digits to a database or mobile applications. This paper proposes a system that can detect the digital number of meter readings using a lightweight deep neural network (DNN) for low power consumption and send those digits to an Android mobile application in real-time to store them and make life easy. The proposed lightweight DNN is computationally inexpensive and exhibits accuracy similar to those of conventional DNNs.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1020-1025
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• 2021

Facial alignment is very important task for human life. And facial landmark detection is one of the instrumental methods in face alignment. We introduce the stacked hourglass networks with transposed convolutional layers for facial landmark detection. our method substitutes nearest neighbor upsampling for transposed convolutional layer. Our method returns better accuracy in facial landmark detection compared to stacked hourglass networks with nearest neighbor upsampling.

• Electronics and Telecommunications Trends
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• v.37 no.4
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• pp.60-69
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• 2022

So far, artificial intelligence (AI)/machine learning (ML) has produced impressive results in speech recognition, computer vision, and natural language processing. AI/ML has recently begun to show promise as a viable means for improving the performance of 5G mobile telecommunication systems. This paper investigates standardization activities in 3GPP and O-RAN Alliance regarding AI/ML applications on mobile telecommunication system. Future trends in AI/ML technologies are also summarized. As an overarching technology in 6G, there appears to be no doubt that AI/ML could contribute to every part of mobile systems, including core, RAN, and air-interface, in terms of performance enhancement, automation, cost reduction, and energy consumption reduction.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.33-45
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• 2023

This paper proposes an algorithm that automatically converts images into Pipo, painting images using OpenCV-based image processing technology. The existing "purity," "palm," "puzzling," and "painting," or Pipo, painting image production method relies on manual work, so customized production has the disadvantage of coming with a high price and a long production period. To resolve this problem, using the OpenCV library, we developed a technique that automatically converts an image into a Pipo painting image by designing a module that changes an image, like a picture; draws a line based on a sector boundary; and writes sector numbers inside the line. Through this, it is expected that the production cost of customized Pipo painting images will be lowered and that the production period will be shortened.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.328-336
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• 2024

Visual communication is widely used and enhanced in modern society, where there is an increasing demand for spirituality. Museum robots are one of many service robots that can replace humans to provide services such as display, interpretation and dialogue. For the improvement of museum guide robots, the paper proposes a human-robot interaction system based on visual communication skills. The system is based on a deep neural mesh structure and utilizes theoretical analysis of computer vision to introduce a Tiny+CBAM mesh structure in the gesture recognition component. This combines basic gestures and gesture states to design and evaluate gesture actions. The test results indicated that the improved Tiny+CBAM mesh structure could enhance the mean average precision value by 13.56% while maintaining a loss of less than 3 frames per second during static basic gesture recognition. After testing the system's dynamic gesture performance, it was found to be over 95% accurate for all items except double click. Additionally, it was 100% accurate for the action displayed on the current page.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.420-426
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• 2001

In this paper, we introduce a case study of developing a miniature humanoid robot that has 16 degrees of freedom and is able to perform statically stable walking. The developed humanoid robot is 37cm tall and weighs 1,200g. RC servo motors are used as actuators. The robot can walk forward and turn to any direction on an even surface. It equipped with a small digital camera, so it can transmit vision data to a remote host computer via wireless modem. The robot can be operated in two modes: One is a remote-controlled mode, in which the robot behaves according to the command given by a human operator through the user-interface program running on a remote host computer, the other is a stand-alone mode, in which the robot behaves autonomously according the pre-programmed strategy. The user-interface program also contains a robot graphic simulator that is used to produce and verify the robot\`s gait motion. In our walking algorithm, the ankle joint is mainly used for balancing the robot. The experimental results shows that the developed robot can perform statically stable walking on an even surface.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.380-385
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• 2016

Shadows are common phenomena observed in natural scenes and often bring a major problem that is affected negatively in colour image analysis. It is important to detect the shadow areas and should be considered in the pre-processing of computer vision. In this paper, the method of shadow detection is proposed using cross entropy and intensity image, and is performed in single image based on the satellite images. After converting the color image to a gray level image, the shadow candidate region has been estimated the optimal threshold value by cross entropy, and then the final shadow region has been detected using intensity image. For the validity of the proposed method, the satellite images is used to experiment. Some experiments are conducted so as to verify the proposed method, and as a result, shadow detection is well performed.

• International Journal of Contents
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• v.13 no.1
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• pp.68-75
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• 2017

Interactive Typography is a process where a user communicates by interacting with text and a moving factor. This research covers interactive typography using real-time response to a user's gesture. In order to form a language-independent system, preprocessing of entered text data presents image data. This preprocessing is followed by recognizing the image data and the setting interaction points. This is done using computer vision technology such as the Harris corner detector and contour detection. User interaction is achieved using skeleton information tracked by a depth camera. By synchronizing the user's skeleton information acquired by Kinect (a depth camera,) and the typography components (interaction points), all user gestures are linked with the typography in real time. An experiment was conducted, in both English and Korean, where users showed an 81% satisfaction level using an interactive typography system where text components showed discrete movements in accordance with the users' gestures. Through this experiment, it was possible to ascertain that sensibility varied depending on the size and the speed of the text and interactive alteration. The results show that interactive typography can potentially be an accurate communication tool, and not merely a uniform text transmission system.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.121-134
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• 2018

The Von Neumann based architecture of the modern computer has dominated the computing industry for the past 50 years, sparking the digital revolution and propelling us into today's information age. Recent research focus and market trends have shown significant effort toward the advancement and application of artificial intelligence technologies. Although artificial intelligence has been studied for decades since the Turing machine was first introduced, the field has recently emerged into the spotlight thanks to remarkable milestones such as AlexNet-CNN and Alpha-Go, whose neural-network based deep learning methods have achieved a ground-breaking performance superior to existing recognition, classification, and decision algorithms. Unprecedented results in a wide variety of applications (drones, autonomous driving, robots, stock markets, computer vision, voice, and so on) have signaled the beginning of a golden age for artificial intelligence after 40 years of relative dormancy. Algorithmic research continues to progress at a breath-taking pace as evidenced by the rate of new neural networks being announced. However, traditional Von Neumann based architectures have proven to be inadequate in terms of computation power, and inherently inefficient in their processing of vastly parallel computations, which is a characteristic of deep neural networks. Consequently, global conglomerates such as Intel, Huawei, and Google, as well as large domestic corporations and fabless companies are developing dedicated semiconductor chips customized for artificial intelligence computations. The AI Processor Research Laboratory at ETRI is focusing on the research and development of super low-power AI processor chips. In this article, we present the current trends in computation platform, parallel processing, AI processor, and super-threaded AI processor research being conducted at ETRI.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.125-132
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• 2014

In this paper, we present marker-less fingertip and brush tracking system with inexpensive web camera. Parallel computation using CUDA is applied to the tracking system. This tracking system can run on inexpensive environment such as a laptop or a desktop and support for real-time application. We also present realistic water-based sign pen drawing model and implementation. The realistic drawing application with our inexpensive real-time fingertip and brush tracking system shows us the art class of the future. The realistic drawing application, along with our inexpensive real-time fingertip and brush tracking system, would be utilized in test-bed for the future high-technology education environment.