• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.3
• /
• pp.317-322
• /
• 2009

If vibration occurs due to fast movement of the robot, the camera image is unstable. No longer the eyes of a robot can not perform the role. Research methods for the stabilization of shaky video is required. The most popular method is to use the motion vector. But, the drawback to this method will require a large amount of operation. And the limits of the embedded robot. Therefore, in real-time transmission of images to be difficult. This paper proposes a motion sensor using the image stabilization. Uses data that is output from the motion sensor. So, not related to the progress of the robot movement is a way to remove it from the video.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.12
• /
• pp.1329-1336
• /
• 2015

Due to the advances in hardware technologies for low-power CMOS cameras, there have been various researches on wireless video sensor network(WVSN) applications including agricultural monitoring and environmental tracking. In such a system, its core technologies include video compression and wireless transmission. Since data of video sensors are bigger than those of other sensors, it is particularly necessary to estimate precisely the traffic after video encoding. In this paper, we present an estimation method for the encoded video traffic in WVSN networks. To estimate traffic characteristics accurately, the proposed method first measures complexities of frames and then applies them to the bit rate estimation adaptively. It is shown by experimental results that the proposed method improves the estimation of bit rate characteristics by more than 12% as compared to the existing method.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.6 no.2
• /
• pp.68-75
• /
• 2011

This paper describes the development of an open source motion sensor emulator. It helps developers to understand the motion sensor and its data better. Through this emulator, the realtime or stored motion sensor data can be applied to the applications that utilize motion sensors. The data of motion sensors which include accelerometer sensor, magnetic field sensor, gyro sensor, GPS, and so on, can be collected by using smart phones or motion sensors. We also describe a visualizer which shows various graphs, video and 3D animations based on the data sent by the emulator. It helps developers to understand motion sensors and how to use the sensors. The developed emulator is compatible with Android sensor simulator.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.2
• /
• pp.110-114
• /
• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.4
• /
• pp.1146-1165
• /
• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.6
• /
• pp.379-383
• /
• 2015

This paper presents an approach to detect object distance with the use of the recently developed low-cost Kinect sensor. The technique is based on Kinect color depth-image processing and can be used to design various computer-vision applications, such as object recognition, video surveillance, and autonomous path finding. The proposed technique uses keypoint feature detection in the Kinect depth image and advantages of depth pixels to directly obtain the feature distance in the depth images. This highly reduces the computational overhead and obtains the pixel distance in the Kinect captured images.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.1
• /
• pp.19-25
• /
• 2024

This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.

• Journal of information and communication convergence engineering
• /
• v.7 no.4
• /
• pp.507-515
• /
• 2009

In this paper, we propose an image signal processor (ISP) for an ultra small HD-grade video sensor with 3A (AWB, AE, and AF) in camera phones that can process 720P/30fps videos. In order to enhance the video quality of the systems, it is necessary to achieve the high performance of the 3A. The proposed AWB algorithm multiplies the adjusted coefficients of color gains to the captured data of white objects. The proposed AE method adopts the index step moving based on the difference between an averaged Y luminance and a target luminance, together with IIR filters with variable time responses. The proposed AF technique controls the focus curve to find the lens position that maximizes the integrated high frequency components in luminance values by using highpass filters. Finally, we compare the image quality captured from our system to the quality of a commercial HD camcorder in order to evaluate the performance of the proposed ISP. The proposed ISP system is also fabricated with 0.18um CMOS flash memory process.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.6
• /
• pp.761-769
• /
• 2012

In this paper, we propose a low-power design strategy to minimize energy-consumption for surveillance and reconnaissance sensor networks. The sensor network consists of many different nodes with various operations such as target detection, packet relay, video monitoring, changing protocols, and etc. Each sensor node consists of sensing, computing, communication, and power components. These components are integrated on a single or multiple boards. Therefore, the power consumption of each component can be different on various operation types. First, we identified the list of components and measured power consumption for them from the first prototype nodes. Next, we focus on which components are the main sources of energy consumption. We propose many energy-efficient approaches to reduce energy consumption for each operation type.

• Proceeding of Spring/Autumn Annual Conference of KHA
• /
• 2008.11a
• /
• pp.407-412
• /
• 2008

The purpose of this study is to find out the preference and the opinion of feminine seniors on the life support appliances(video phone, medication dispenser, activity monitor and sleep monitor). The appliances may be improved reflecting the result of the preferred functions and designs. The respondents were 141 feminine seniors of 65 years & older, living in Ulsan city or Cheongju city, Korea. Following is the result. 1) All the responses answered that the medication dispenser, video phone and activity monitor, sleep monitor are useful appliances. 2) All the seniors expressed prefer to function of the appliances, and were highly concerned about the price, safety and convenience. 3)The preferred designs were (1) white or red standing medication dispenser,(2) wall-mounted video phone working by voice, (3) metal activity monitor sensor like white or yellow bracelet.