• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.17-22
• /
• 2002

This paper is concerned with a local detection of road on an airborne SAR image. The roads can be characterized by their geometry and radiometry. Roads are assumed as linear, thin, and elongated objects that are darker than their surroundings on an airborne SAR image. With these assumptions, a series of morphological filters are applied and tested successively. This approach is simple and almost non parametric and has been successfully applied to an airborne SAR image.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.12
• /
• pp.1205-1211
• /
• 2008

This paper describes methods to estimate 3-D position of target with respect to reference frame through monocular image from unmanned aerial vehicle (UAV). 3-D position of target is used as information for surveillance, recognition and attack. In this paper. 3-D position of target is estimated to make guidance and control law, which can follow target, user interested. It is necessary that position of target is measured in image to solve 3-D position of target. In this paper, kalman filter is used to track and output position of target in image. Estimation of target's 3-D position is possible using result of image tracking and information of UAV and camera. To estimate this, two algorithms are used. One is methode from arithmetic derivation of dynamics between UAV, carmer, and target. The other is LPV (Linear Parametric Varying). These methods have been run on simulation, and compared in this paper.

• The Journal of Korean Association of Computer Education
• /
• v.11 no.5
• /
• pp.57-66
• /
• 2008

An adaptive optimization of parametric cubic convolution for image interpolation is derived in this paper. The proposed technique is based on optimizing the standard cubic convolution interpolation formula at each interpolated pixel. Conventional parametric cubic convolution methods use a fixed parameter in an image, so properties of each pixel cannot be incorporated into the interpolation. The proposed method optimizes the interpolation kernel by obtaining parameters adaptively on each pixel. A new cost function is introduced to reflect frequency properties of the original data. The proposed technique produces noticeably sharper edges than traditional techniques and exhibits an average PSNR improvement of traditional techniques.

• Proceedings of the KOSOMBE Conference
• /
• v.1996 no.05
• /
• pp.279-282
• /
• 1996

Sequential brain SPECT imaging has been used to assess the cerebral perfusion reserve(CPR) in cerebrovascular diseases(CVD). We have realized a parametric images of CPR using normalized difference ratio and deadtime correction. For the anatomical localization of CPR, the parametric images were registered to the contours of the cerebral regions using optimal threshold method. The parametric imags reflected the CPR more reliably and distinctively. We conclude that the qunatitative estimation of CPR using normalized difference ratio image could be useful for the diagnosis and assessment of postoperative prognosis in CVD.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.24 no.1
• /
• pp.159-166
• /
• 1987

A new family of sinusoidal orthogoal trnasform is introduced. For a derivation, a parametric sinusoidal matrix whose transform might be implemented by a suitable FFT algorithm is modeled basically on the analogy of well-known sinusoidal transform such as DCT,SCT, etc., and its orthogonality condition is calculated. The parameters satisfying orthogonality condition are determined, in a sense, by particular solution after trial and error. However more than then transform matrices not yet known are obtained. It is also shown that these transforms can be computed by a DFT. of an image.

• IEIE Transactions on Smart Processing and Computing
• /
• v.5 no.5
• /
• pp.319-322
• /
• 2016

We propose a parametric blind deconvolution method for bi-level images with unknown intensity levels that estimates unknown parameters for point spread functions and images by minimizing a penalized nonlinear least squares objective function based on normalized correlation coefficients and two regularization functions. Unlike conventional methods, the proposed method does not require knowledge about true intensity values. Moreover, the objective function of the proposed method can be effectively minimized, since it has the special structure of nonlinear least squares. We demonstrate the effectiveness of the proposed method through simulations and experiments.

• Journal of Biomedical Engineering Research
• /
• v.17 no.4
• /
• pp.443-448
• /
• 1996

Sequential brain SPECT imaging has been used to assess the cerebral perfusion reserve(CPR) in cerebrovascular diseases(UD). We have realized parametric images of CPR using deadtime correction of gamma camera and normalized difference ratio. For the anatomical localization of CPR, the parametric images were registered to the contours of the cerebral regions using optimal threshold method, which showed to reflect the CPR more reliably and distinctively than the simple subtraction. We conclude that the quantitative estimation of CPR using normalized difference ratio image could be useflll for the diagnosis and prognostic assessment of CVD.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.10C
• /
• pp.1013-1022
• /
• 2003

This paper implemented the real-time object tracking algorithm that extracts and tracks the moving object adaptively to input frame sequence by using non-parametric image processing method and Kalman filter-based dynamic AR(2) process method. By applying non-parametric image processing to input frames, the moving object was extracted from the background adaptively to diverse environmental conditions. And the movement of object was able to be adaptively estimated and tracked by modeling the various movement of object as dynamic AR(2) process and estimating based on the Kalman filter the parameters of AR(2) process dynamically changing along time. The experiments of the implemented object tracking system showed that the proposed method tracked the moving object as more approximately as the estimation error became about l/2.5∼1/50 of one of the traditional tracking method based on linear Kalman filter.

• KSTLE International Journal
• /
• v.2 no.1
• /
• pp.35-39
• /
• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.628-631
• /
• 2009

In this paper, we proposed a new authentication method using video that was taken during moving a hand-held camera in front of the face. The proposed method extracted individuality from the obtained image sequences using the parametric eigenspace scheme. Changes of facial appearance through authentication trials draw continuous tracks in the low dimensional igenspace. The similarity between their continuous tracks are calculated by DP-matching to verify their identities. Experimental results confirmed that different motions and persons change the shapes of continuous tracks, so the proposed method could identify the person.