• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.42-47
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• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.79-86
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• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• Imaging Science in Dentistry
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• v.41 no.4
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• pp.143-150
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• 2011

Purpose : The aim of this study was to compare the diagnostic accuracy of cone-beam computed tomography (CBCT) images and bitewing images in detection of secondary caries. Materials and Methods : One hundred and twenty proximal slots of Class II cavities were randomly prepared on human premolar and molar teeth, and restored with amalgam (n=60) and composite resin (n=60). Then, artificial secondary caries lesions were randomly created using round steel No. 4 bur. The teeth were radiographed with a conventional bitewing technique and two CBCT systems; Pax-500ECT and Promax 3D. All images were evaluated by five observers. The area under the receiver operating characteristic (ROC) curve ($A_z$) was used to evaluate the diagnostic accuracy. Significant difference was tested using the Friedman test (p value<0.05). Results : The mean $A_z$ values for bitewing, Pax-500ECT, and Promax 3D imaging systems were 0.882, 0.995, and 0.978, respectively. Significant differences were found between the two CBCT systems and film (p=0.007). For CBCT systems, the axial plane showed the greatest $A_z$ value. Conclusion : Based on the design of this study, CBCT images were better than bitewing radiographs in detection of secondary caries.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2843-2845
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• 2000

A lane detection based on a road model or feature all need correct acquirement of information on the lane in a image, It is inefficient to implement a lane detection algorithm through the full range of a image when being applied to a real road in real time because of the calculating time. This paper defines two searching range of detecting lane in a road, First is searching mode that is searching the lane without any prior information of a road, Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It is allow to extract accurately and efficiently the edge candidates points of a lane as not conducting an unnecessary searching. By means of removing the perspective effect of the edge candidate points which are acquired by using the inverse perspective transformation, we transform the edge candidate information in the Image Coordinate System(ICS) into the plane-view image in the World Coordinate System(WCS). We define linear approximation filter and remove the fault edge candidate points by using it This paper aims to approximate more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.

• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.105-110
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• 2015

This paper presents a $4{\times}1$ beam-forming reader antenna system for a new type of RFID based train position detection technology. The required beamwidth of the reader antenna is analytically expressed for different train speeds. The proposed antenna system consists of four rectangular patch elements and two switching couplers which are designed, without any impedance matching networks, for two different antenna modes. The switching coupler is a rectangular quadrature coupler with Pin diodes connecting its center line and the ground plane. The beamwidth of the antenna when the diodes are off and on is $18^{\circ}$ and $39^{\circ}$, respectively. The proposed antenna system will be used for a real train test in the near future.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.395-399
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• 2006

A method to recognize unpaved road region using a 3D depth measurement system is proposed for mobile robots. For autonomous maneuvering of mobile robots, recognition of obstacles or recognition of road region is the essential task. In this paper, the 3D depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Therefore, the problem falls into a texture identification problem. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of unpaved trail are included in this paper.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.133-134
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• 2014

Conventional stereo matching algorithms fail when they deal with anaglyph image as its input because anaglyph image does not have similar intensity on both view images. To ameliorate such problems, we propose a robust method to obtain accurate disparity maps. The novel Absolute Adaptive Normalized Cross Correlation (AANCC) for anaglyph data cost is introduced in this paper. Then, it is followed by occlusion detection and segmentation-based plane fitting to achieve accurate depth map acquisition. Experimental results confirm that the proposed anaglyph data cost is robust and gives accurate disparity maps.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1666-1671
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• 2002

A lane sensing algorithm using vision sensors is developed based on lane geometry models. The parameters of the lane geometry models are estimated by a Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from image plane to global coordinate assumes earth to be flat, but roll and pitch motions of a vehicle are considered from the perspective of the lane sensing. The proposed algorithm shows robust lane sensing performance compared to the conventional algorithms.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.4 s.19
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• pp.79-86
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• 2004

This paper has presented to the design results of the analog and digital signal processor for the 2nd generation thermal imaging system using $480\times6$ infrared focal plane array In order to correct non-uniformities of detector arrays, we have developed the 2-point correction method using the thermo electric cooler. Additionally, to enhance the image of low contrast and improve the detection capability, we developed the new technique of histogram processing being suitable for the characteristics of contrast distribution of thermal imagery. Through these image processing techniques, we obtained a high qualify thermal image and acquired good result.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04c
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• pp.6-9
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• 2008

A 3D depth measurement system is proposed for mobile vehicles. Depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to- the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of Non-linear trail are included in this paper.