• Proceedings of the KSRS Conference
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• v.2
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• pp.772-775
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• 2006

Muilti-dimensional feature vector matching algorithm uses multiple features such as intensity, gradient, variance, first or second derivative of a pixel to find correspondence pixels in stereo images. In this paper, we proposed a new method for adjusting automatically the weight of feature in multi-dimensional feature vector matching considering sharpeness of a pixel in feature vector distance curve. The sharpeness consists of minimum and maximum vector distances of a small window mask. In the experiment we used IKONOS satellite stereo imagery and obtained accurate matching results comparable to the manual weight-adjusting method.

• Journal of Sensor Science and Technology
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• v.24 no.3
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• pp.202-207
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• 2015

As a feasibility study on development of a gamma imaging probe, we developed a scintillating film-based gamma imaging detector that can obtain scintillation images with information of gamma-ray distribution. The scintillating film-based gamma imaging detector was composed of a sensing probe, an image intensifier, and a beam profiler. To detect and transmit scintillation image, the sensing probe was fabricated by coupling a scintillating film, a fiber-optic image conduit, and a fiber-optic taper, consecutively. First, the optical images of USAF 1951 resolution target were obtained and then, modulation transfer function values were calculated to test the image quality of the sensing probe. Second, we measured the scintillation images according to the activity of the 137Cs and the distance between the surface of 137Cs and the distal-end of sensing probe. Finally, the intensities of scintillating light as functions of the activity and the distance were evaluated from the region of interest in the scintillation image. From the results of this study, it is expected that a fiber-optic gamma imaging detector can be developed to detect gamma-rays emitted from radiopharmaceuticals during radioimmunoguided surgery.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1555-1570
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• 2016

For monitoring forest fires, a real-time system to prevent fires in wider areas should be supported consistently. However, there has still been a lack of the support for real-time system related to forest fire monitoring. In addition, the 'real-time' processing in a forest fire detection system can lead to excessive consumption of energy. To solve these problems, the intelligent data acquisition of sensing nodes is required, and the maximum energy savings as well as rapid and accurate detection by flame sensors need to be done. In this regard, this paper proposes a node built-in filter algorithm for intelligent data collection of sensing nodes for the rapid detection of forest fires with focus on reducing the power consumption of the remote sensing nodes and providing efficient wireless sensor network-based forest environment monitoring in terms of data transmission, network stability and data acquisition. The experimental result showed that battery life can be extended through the intelligent sampling of remote sensing nodes, and the average accuracy of the measurement of flame detection based on the distance is 44%.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.1-9
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• 2015

Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

• Journal of Sensor Science and Technology
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• v.22 no.6
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• pp.393-399
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• 2013

We propose a method of sensing the rotation and distance of a camera by using a fisheye lens system as a vision sensor. We estimate the rotation angle of a camera with a modified correlation method by clipping similar regions to avoid symmetry problems and suppressing highlight areas. In order to eliminate the rectification process of the distorted points of a fisheye lens image, we introduce an offline process using the normalized focal length, which does not require the image sensor size. We also formulate an equation for calculating the distance of a camera movement by matching the feature points of the test image with those of the reference image.

• Journal of IKEEE
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• v.22 no.4
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• pp.907-915
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• 2018

This paper proposes a method to improve the performance of low cost infrared distance sensor. Infrared distance sensor measures the intensity of reflected light and converts it into distance. The proposed method improves the sensing distance of the sensor and makes it operate robustly in various lighting environments. This is achieved by extracting the characteristic curves of the sensor and applying the HDR (High Dynamic Range) technique. The output value of the sensor was obtained by varying the intensity of the infrared input and the exposure time, and the characteristic curve of the sensor was extracted from it.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.47-56
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• 1997

In this paper, remote sensing is used to estimate trophic state which is primary concern in a lake. In using remote sensing, this study estimated trophic state not with conventional method such as regression equations but with classification methods. As europhication is caused by the extraodinary proliferation of the algae, chlorophyll a and transparency are applied to remote sensing data.. Maximum Likelihood Classification and Minimum Distance Classification which are kinds of classification methods enabled trophic state to be confirmed in a lake. These are obtained as the result of applying remote sensing to classify trophic state in a lake. Firest, when we evaluate tropic state in a large area of water body, the application of remote sensing data can obtain more than 70% accuracies just in using basic classification methods. Second, in the aspect of classification, the accuracy of Minimum Distance Classification is usually better than that of Maximum Likelihood Classification. This result is caused that samples have normal distribution, but their numbers are a few to apply statistical method. Therefore, classification method is required such as artificial neural networks which are not influenced by statistical distribution. Third, this study enables the trophic state of water body to be analyzed and evaluated rapidly, periodically and visibly. Also, this study is good for forming proper countermeasure accompanying with trophic state progress extent in a lake and is useful for basic-data.

• Current Optics and Photonics
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• v.5 no.3
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• pp.298-305
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• 2021

Modern distance sensing methods employ various measurement principles, including triangulation, time-of-flight, confocal, interferometric and frequency comb. Among them, the triangulation method, with a laser light source and an image sensor, is widely used in low-cost applications. We developed an omnidirectional two-dimensional (2D) distance sensor based on the triangulation principle for indoor floor mapping applications. The sensor has a range of 150-1500 mm with a relative resolution better than 4% over the range and 1% at 1 meter distance. It rotationally scans a compact one-dimensional (1D) distance sensor, composed of a near infrared (NIR) laser diode, a folding mirror, an imaging lens, and an image detector. We designed the sensor layout and configuration to satisfy the required measurement range and resolution, selecting easily available components in a special effort to reduce cost. We built a prototype and tested it with seven representative indoor wall specimens (white wallpaper, gray wallpaper, black wallpaper, furniture wood, black leather, brown leather, and white plastic) in a typical indoor illuminated condition, 200 lux, on a floor under ceiling mounted fluorescent lamps. We confirmed the proposed sensor provided reliable distance reading of all the specimens over the required measurement range (150-1500 mm) with a measurement resolution of 4% overall and 1% at 1 meter, regardless of illumination conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.454-461
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• 2000

Electrostatic suspension offers an advantage of directly suspending various materials such as conductive materials, semiconductors and dielectric materials without any mechanical contacts. This is a specific feature compared with electromagnetic suspension which can suspend only ferro-magnetic material. In general, the electrostatic suspension systems require position sensors for stabilizing the suspended object. Therefore, a lot of displacement sensors and a switching circuit are required for moving the object through a long distance. In order to circumvent this problem, this paper proposes a self-sensing method which can provide the gap displacement between electrodes and suspended object without external sensors. Moreover a simple on-off controller is presented for stabilization. Experimental validation of the proposed scheme has been performed through the successful levitation of a 4-inch silicon wafer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.520-541
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• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.