• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.5
• /
• pp.2414-2433
• /
• 2019

The aim of this paper is to design a 3D laser radar prototype based on laser triangulation. The mathematical model of distance sensitivity is deduced; a pixel-distance conversion formula is discussed and used to complete 3D scanning. The center position extraction algorithm of the spot is proposed, and the error of the linear laser, camera distortion and installation are corrected by using the proposed weighted average algorithm. Finally, the three-dimensional analytic computational algorithm is given to transform the measured distance into point cloud data. The experimental results show that this 3D laser radar can accomplish the 3D object scanning and the environment 3D reconstruction task. In addition, the experiment result proves that the product of the camera focal length and the baseline length is the key factor to influence measurement accuracy.

• Journal of Digital Convergence
• /
• v.13 no.11
• /
• pp.165-170
• /
• 2015

The Vocabulary Recognition System made by recognizing the standard vocabulary is seen as a decline of recognition when out of the standard or similar words. The vector values of the existing system to the model created by configuring the database was used in the recognition vocabulary. The model to be formed during the search for the recognition vocabulary is recognizable because there is a disadvantage not configured with a database. In this paper, it induced to recognize the vector model is formed by the search and configuration using a Bayesian model recognizes the Bhattacharyya distance measurement based on the vector model, by applying the Wiener filter improves the recognition rate. The result of Convergence of two method's are improved reliability experiments for distance measurement. Using a proposed measurement are compared to the conventional method exhibited a performance of 98.2%.

• International journal of advanced smart convergence
• /
• v.5 no.2
• /
• pp.53-58
• /
• 2016

With the growing use of big data and data mining, it serves to understand how such techniques can be used to understand various relationships in the healthcare field. This study uses hierarchical methods of data analysis to explore similarities in hospitalization across several New York state counties. The study utilized methods of measuring crowding distance of data for age-specific hospitalization period. Crowding distance is defined as the longest distance, or least similarity, between urban cities. It is expected that the city of Clinton have the greatest distance, while Albany the other cities are closer because they are connected by the shortest distance to each step. Similarities were stronger across hospital stays categorized by age. Hierarchical clustering can be applied to predict the similarity of data across the 10 cities of hospitalization with the measurement of crowding distance. In order to enhance the performance of hierarchical clustering, comparison can be made across congestion distance when crowding distance is applied first through the application of converting text to an attribute vector. Measurements of similarity between two objects are dependent on the measurement method used in clustering but is distinguished from the similarity of the distance; where the smaller the distance value the more similar two things are to one other. By applying this specific technique, it is found that the distance between crowding is reduced consistently in relationship to similarity between the data increases to enhance the performance of the experiments through the application of special techniques. Furthermore, through the similarity by city hospitalization period, when the construction of hospital wards in cities, by referring to results of experiments, or predict possible will land to the extent of the size of the hospital facilities hospital stay is expected to be useful in efficiently managing the patient in a similar area.

• Phonetics and Speech Sciences
• /
• v.12 no.3
• /
• pp.25-32
• /
• 2020

An analysis of emotional English utterances with 7 emotions (calm, happy, sad, angry, fearful, disgust, surprised) was conducted using the measurement of prosodic distance between 672 emotional and 48 neutral utterances. Applying the technique proposed in the automatic evaluation model of English pronunciation to the present study on emotional utterances, Euclidean distance measurement of 3 prosodic elements such as F0, intensity and duration extracted from emotional and neutral utterances was utilized. This paper, furthermore, extended the analytical methods to include Euclidean distance normalization, z-score and z-score normalization resulting in 4 groups of measurement schemes (sqrF0, sqrINT, sqrDUR; norsqrF0, norsqrINT, norsqrDUR; sqrzF0, sqrzINT, sqrzDUR; norsqrzF0, norsqrzINT, norsqrzDUR). All of the results from perceptual analysis and acoustical analysis of emotional utteances consistently indicated the greater effectiveness of norsqrF0, norsqrINT and norsqrDUR, among 4 groups of measurement schemes, which normalized the Euclidean measurement. The greatest acoustical change of prosodic information influenced by emotion was shown in the values of F0 followed by duration and intensity in descending order according to the effect size based on the estimation of distance between emotional utterances and neutral counterparts. Tukey Post Hoc test revealed 4 homogeneous subsets (calm

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.5
• /
• pp.85-91
• /
• 2009

Because ubiquitous environment has come with growing IT technology, Researches wireless sensor network are actively on going in many aspects. In this paper, we proposed simple method of distance measurement for omnidirectional distance calculation in wireless sensor network. In addition, we design and implement the proposed method. Then, we verify it through experiments at real environments. when we use the proposed method, maximum distance of measurement is decreased, but we measure distance from degrees. In this paper, we show drop rate and accuracy rate of ultrasonic distance estimation with and without omnidirectional device through experiments at real environments.

• Journal of IKEEE
• /
• v.26 no.2
• /
• pp.169-175
• /
• 2022

This paper introduces an interference elimination method using k-nearest neighbor (KNN) algorithm for precise distance estimation by reducing interference between ultrasonic sensors. Conventional methods compare current distance measurement result with previous distance measurement results. If the difference exceeds some thresholds, conventional methods recognize them as interference and exclude them, but they often suffer from imprecise distance prediction. KNN algorithm classifies input values measured by multiple ultrasonic sensors and predicts high accuracy outputs. Experiments of distance measurements are conducted where interference frequently occurs by multiple ultrasound sensors of same type, and the results show that KNN algorithm significantly reduce distance prediction errors. Also the results show that the prediction performance of KNN algorithm is superior to conventional voting methods.

• Journal of the Economic Geographical Society of Korea
• /
• v.17 no.1
• /
• pp.98-113
• /
• 2014

The purpose of this study is to investigate the changes in the accessibility of the Metropolitan Seoul Transit systems since 2000, in which many new subway lines have been constructed as well as other urban transit lines have been connected to the systems. We suggest an accessibility measure model for Un-fixed Transportation Networks. In order to measure the nodal accessibility based on the mobility, we apply path-distance, physical-distance, and time-distance as the distance impedance measurement. Specifically, we develop time-distance algorithms to measure the time-distance between each pairs of transit stations based on the T-card transaction databases. We apply the model to the Metropolitan Seoul Transit systems in two time points(2005 and 2011). We examine the results in terms of three distance accessibility measures. Time-distance accessibility explains better the urban land use patterns in the Metropolitan Seoul area than the other two. We visualize the spatial patterns of time-distance accessibility by applying GIS, and analyze the spatial structures of accessibility in the Metrropolitan Seoul area between two time points.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.28 no.3
• /
• pp.74-82
• /
• 2024

In this study, feature point detection and displacement measurement performance depending on feature extraction algorithms were compared and analyzed according to environmental changes and target types in the feature point-based displacement measurement algorithm. A three-story frame structure was designed for performance evaluation, and the displacement response of the structure was digitized into FHD (1920×1080) resolution. For performance analysis, the initial measurement distance was set to 10m, and increased up to 40m with an increment of 10m. During the experiments, illuminance was fixed to 450lux or 120lux. The artificial and natural targets mounted on the structure were set as regions of interest and used for feature point detection. Various feature detection algorithms were implemented for performance comparisons. As a result of the feature point detection performance analysis, the Shi-Tomasi corner and KAZE algorithm were found that they were robust to the target type, illuminance change, and increase in measurement distance. The displacement measurement accuracy using those two algorithms was also the highest. However, when using natural targets, the displacement measurement accuracy is lower than that of artificial targets. This indicated the limitation in extracting feature points as the resolution of the natural target decreased as the measurement distance increased.

• Journal of Digital Convergence
• /
• v.10 no.3
• /
• pp.265-271
• /
• 2012

This paper proposes a communication distance performance evaluation method for mobility of service robots equipped with a Wi-Fi module. Service robots have function of mobile communication system according to classified services and utilize a (preferred) communication method, wireless lan(IEEE802.11 a/b/gin) communication method of ISM band(2.4GHz and 5.8GHz). For evaluating degradation performance of wireless data for the service robot's mobility. We measured and presented reference vectors obtained by utilizing a distance attenuation correlation method in the real world environment. To evaluate performance of the proposed method, path loss of reference vectors was assigned to the Azimuth 301W and then transmission rate and the transmit throughput of the test sample were measured by the Chariot. The proposed measurement method is necessary for securing wireless LAN communication distance for mobility of mobile smart device and service robots. In addition, if the proposed measurement method os adopted, It would be expected that mobile smart device vendors would utilize the method as an effective wireless LAN mobility communication distance performance evaluation method.