• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.46-50
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• 2014

In this paper, we report a novel algorithm based on phase displacement, which supplements conventional TOF methods for distance measurement using an ultrasonic wave. The proposed algorithm roughly measures the distance between the transmission part and the receiving part by using the initial TOF. Thereafter, the precise distance is determined by measuring the phase displacement value between the synchronizing transmission signal and the signal obtained at the receiving end. A distance measurement experiment using a micrometer was performed to verify the accuracy of the ultrasonic wave sensor system. We found that the mean errors from the one adopting the distance measurement algorithm based on phase displacement varied from a minimum of 0.03 mm to a maximum of 0.09 mm. In addition, the standard deviation varied from a minimum of 0.04 mm to a maximum of 0.07 mm, thus giving a precision of ${\pm}0.1$ mm.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.343-347
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• 2010

This paper presents an efficient image recognition method using the hybrid coefficient measure of correlation and distance. The correlation coefficient is applied to measure the statistical similarity by using Pearson coefficient, and distance coefficient is also applied to measure the spacial similarity by using city-block. The total similarity among images is calculated by extending the similarity between the feature vectors, then the feature vectors can be extracted by PCA and ICA, respectively. The proposed method has been applied to the problem for recognizing the 960(30 persons * 4 expressions * 2 lights * 4 poses) facial images of 40*50 pixels. The experimental results show that the proposed method of ICA has a superior recognition performances than the method using PCA, and is affected less by the environmental influences so as lighting.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.85-87
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• 2000

In pattern classification, the Bhattacharyya distance has been used as a class separability measure and provides useful information for feature selection and extraction. In this paper, we propose a method to predict the classification error for multimodal data based on the Bhattacharyya distance. In our approach, we first approximate the pdf of multimodal distribution with a Gaussian mixture model and find the bhattacharyya distance and classification error. Exprimental results showed that there is a strong relationship between the Bhattacharyya distance and the classification error for multimodal data.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.223-232
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• 2003

This paper presents a new method driving multiple robots to their goal position without collision. Each robot adjusts its motion based on the information on the goal location, velocity, and position of the robot and the velocity and position of the .other robots. To consider the movement of the robots in a work area, we adopt the concept of avoidability measure. The avoidability measure figures the degree of how easily a robot can avoid other robots considering the following factors: the distance from the robot to the other robots, velocity of the robot and the other robots. To implement the concept in moving robot avoidance, relative distance between the robots is derived. Our method combines the relative distance with an artificial potential field method. The proposed method is simulated for several cases. The results show that the proposed method steers robots to open space anticipating the approach of other robots. In contrast, the usual potential field method sometimes fails preventing collision or causes hasty motion, because it initiates avoidance motion later than the proposed method. The proposed method can be used to move robots in a robot soccer team to their appropriate position without collision as fast as possible.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1493-1503
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• 2018

We propose an object recognition system and experiential game contents using Kinect to maximize object recognition rate by utilizing underwater robots. we implement an ice hockey game based on object-aware interactive contents to validate the excellence of the proposed system. The object recognition system, which is a preprocessor module, is composed based on Kinect and OpenCV. Network sockets are utilized for object recognition communications between C/S. The problem of existing research, degradation of object recognition at long distance, is solved by combining the system development method suggested in the study. As a result of the performance evaluation, the underwater robot object recognized all target objects (90.49%) with 80% of accuracy from a 2m distance, revealing 42.46% of F-Measure. From a 2.5m distance, it recognized 82.87% of the target objects with 60.5% of accuracy, showing 34.96% of F-Measure. Finally, it recognized 98.50% of target objects with 59.4% of accuracy from a 3m distance, showing 37.04% of F-measure.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.789-793
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• 2005

Interval-valued fuzzy sets were suggested for the first time by Gorzalczang(1983) and Turken(19a6). Based on this, Wang and Li offended their operations on interval-valued fuzzy numbers. Recently, Hong(2002) generalized results of Wang and Li and extended to interval-valued fuzzy sets with Riemann integral. In this paper, using Choquet integrals with respect to a fuzzy measure instead of Riemann integrals with respect to a classical measure, we define a Choquet distance measure for interval-valued fuzzy numbers and investigate its properties.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.125-136
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• 2007

The study on query relaxation which provides approximate answers has received attention. In recent years, some arguments have been made that semantic relationships are useful to present the relationships among data values and calculating the semantic distance between two data values can be used as a quantitative measure to express relative distance. The aim of this article is a hierarchical metricized knowledge abstraction (HiMKA) with an emphasis on combining data abstraction hierarchy and distance measure among data values. We propose the operations and the query relaxation algorithm appropriate to the HiMKA. With various experiments and comparison with other method, we show that the HiMKA is very useful for the quantified approximate query answering and our result is to offer a new methodological framework for query relaxation.

• International Journal of Contents
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• v.5 no.4
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• pp.51-54
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• 2009

In huge video databases, the effective video content indexing method is required. While manual indexing is the most effective approach to this goal, it is slow and expensive. Thus automatic indexing is desirable and recently various indexing tools for video databases have been developed. For efficient video content indexing, the similarity measure is an important factor. This paper presents new similarity measures between frames and proposes a new algorithm to index video content using Kullback-Leibler distance defined between two histograms. Experimental results show that the proposed algorithm using Kullback-Leibler distance gives remarkable high accuracy ratios compared with several conventional algorithms to index video content.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.74-80
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• 2015

In cognitive radios, spectrum sensing plays an important role in accurately detecting the presence or absence of a licensed user. However, the intervention of malicious users (MUs) degrades the performance of spectrum sensing. Such users manipulate the local results and send falsified data to the data fusion center; this process is called spectrum sensing data falsification (SSDF). Thus, MUs degrade the spectrum sensing performance and increase uncertainty issues. In this paper, we propose a method based on the Hausdorff distance and a similarity measure matrix to measure the difference between the normal user evidence and the malicious user evidence. In addition, we use the Dempster-Shafer theory to combine the sets of evidence from each normal user evidence. We compare the proposed method with the k-means and Jaccard distance methods for malicious user detection. Simulation results show that the proposed method is effective against an SSDF attack.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.679-684
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• 2019

We propose a method to measure the number of specific species of class using CAFFE model and a method to measure length and width of object using stereo vision. To obtain the width of an object, the location coordinates of objects appearing on the left and right sensor is compared and the distance from the sensor to the object is obtained. Then the length of the object in the image by using the distance and the approximate value of the actual length of the object is calculated.