• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2461-2466
• /
• 2003

This paper presents a simple sensor fusion algorithm using neural network for navigation of mobile robots with obstacle avoidance and trap recovery. The multiple sensors input sensor data to the input layer of neural network activating the input nodes. The multiple sensors used include optical encoders, ultrasonic sensors, infrared sensors, a magnetic compass sensor, and GPS sensors. The proposed sensor fusion algorithm is combined with the VFH(Vector Field Histogram) algorithm for obstacle avoidance and AGPM(Adaptive Goal Perturbation Method) which sets adaptive virtual goals to escape trap situations. The experiment results show that the proposed low-level fusion algorithm is effective for real-time navigation of mobile robot.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.4
• /
• pp.281-286
• /
• 2010

We propose a space and time based sensor fusion method and a robust landmark detecting algorithm based on sensor fusion for mobile robot navigation. To fully utilize the information from the sensors, first, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to landmark recognition for mobile robot navigation in an unstructured environment as well as structured environment, and the experimental results demonstrate the performances of the landmark recognition.

• Journal of Information Technology Applications and Management
• /
• v.9 no.3
• /
• pp.1-12
• /
• 2002

Due to the fast development in computer and communication technologies, a video is now being more widely used than ever in many areas. The current information analyzing systems are originally built to process text-based data. Thus, it has little bits problems when it needs to correctly represent the ambiguity of a video, when it has to process a large amount of comments, or when it lacks the objectivity that the jobs require. We would like to purpose an algorithm that is capable of analyze a large amount of video efficiently. In a video, divided areas use a region growing and region merging techniques. To sample the color, we translate the color from RGB to HSI and use the information that matches with the representative colors. To sample the shape information, we use improved moment invariants(IMI) so that we can solve many problems of histogram intersection caused by current IMI and Jain. Sampled information on characteristics of the streaming media will be used to find similar frames.

• Journal of Advanced Marine Engineering and Technology
• /
• v.12 no.3
• /
• pp.43-56
• /
• 1988

The image processing system consisted of the microcomputer IBM PC-XT and the graphic board (16 gray level and $640{\times}400$ pixels resolution) has been proposed, and the image processing softwares programmed in the BASIC and in the assembler language have been developed. The programs are consisted of the main menu and the sub menu, that have contained the subroutine for the capture for image data, the determination of region, the histogram, the change of value, the montage, the skeleton, the mask, the moving, the zoom, the disk access and the print. For the application, the photoelastic fringe data have been captured and analyzed. It was seen that the programs are available for the image processing.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.4
• /
• pp.304-308
• /
• 2001

The increase of video data makes the demand of efficient retrieval, storing, and browsing technologies necessary. In this paper, a video segmentation method (scene change detection method, or shot boundary detection method) for the development of such systems is proposed. For abrupt cut detection, inter-frame similarities are computed using luminance and edge histograms and a cut is declared when the similarities are under th predetermined threshold values. A gradual scene change detection is based on the similarities between the current frame and the previous shot boundary frame. A correlation method is used to obtain universal threshold values, which are applied to various video data. Experimental results show that propose method provides 90% precision and 98% recall rates for abrupt cut, and 59% precision and 79% recall rates for gradual change.

• ETRI Journal
• /
• v.41 no.6
• /
• pp.782-796
• /
• 2019

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large-scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi-Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.9
• /
• pp.922-928
• /
• 2009

This thesis puts forward a suggestion of measuring inner crack and center segregation in steel processing by using scanner and image processing with sulfur printer. To sum up, there are three points in this system. First, it scans sulfur printer and process the image by using histogram, image processing, and the mask. Second, it measures crack and center segregation by the fictitious image and output the length, thickness, exponent and grade on the mornitor. And finally, it gathers the measurement result image and data at the server and this information is used as data for the next casting.

• Journal of the Semiconductor & Display Technology
• /
• v.7 no.2
• /
• pp.69-76
• /
• 2008

Recently, as the multimedia processing application increases rapidly by going on increasing multimedia data, the efficient retrieval method of image information is required in many fields of application and becoming the matter of major concern. Furthermore, in the last few years rapid improvements in hardware technology have made it possible to process, store and retrieve huge amounts of data in a multimedia format. As a result, Content-Based Image Retrieval (CBIR) has been receiving widespread interest during the last decade. This paper propose the content-based retrieval system as a method for performing image retrieval through the effective feature analysis of the object of significant meaning by using YCbCr channel merging on the basis of the characteristics of man's visual system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.4
• /
• pp.457-467
• /
• 1993

One of the important statistical quantities for optical waves through random media is the probability distribution of irradiance. From phenomenological models, several distribution functions have been proposed. In this paper, irradiance data are obtained by computer simulation, and by comparing the proposed distribution functions with simulation data by the moment method, the histogram method, and the $x^2$-test, the validity of each distribution function is investigated.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.26 no.4
• /
• pp.263-279
• /
• 2022

This paper presents an automatic inspection of defects in semiconductor images. We devise a statistical method to find defects on homogeneous background from the observation that it has a log-normal distribution. If computer aided design (CAD) data is available, we use it to construct a signed distance function (SDF) and change the pixel values so that the average of pixel values along the level curve of the SDF is zero, so that the image has a homogeneous background. In the absence of CAD data, we devise a hybrid method consisting of a model-based algorithm and two neural networks. The model-based algorithm uses the first right singular vector to determine whether the image has a linear or complex structure. For an image with a linear structure, we remove the structure using the rank 1 approximation so that it has a homogeneous background. An image with a complex structure is inspected by two neural networks. We provide results of numerical experiments for the proposed methods.