• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.1-14
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• 2000

The rosette-scan seeker, mounted on the infrared guided missile, is a device that tracks the target It can acquire the 2D image of the target by scanning a space about target in rosette pattern with a single detector Since the detected image is changed according to the position of the object in the field of view and the number of the object is not fixed, the unsupervised methods are employed in clustering it The conventional ISODATA method clusters the objects by using the distance between the seed points and pixels So, the clustering result varies in accordance with the shape of the object or the values of the merging and splitting parameters In this paper, we propose an Array Linkage Clustering Algorithm (ALCA) as a new clustering algorithm improving the conventional method The ALCA has no need for the initial seed points and the merging and splitting parameters since it clusters the object using the connectivity of the array number of the memory stored the pixel Therefore, the ALCA can cluster the object regardless of its shape With the clustering results using the conventional method and the proposed one, we confirm that our method is better than the conventional one in terms of the clustering performance We simulate the rosette scanning infrared seeker (RSIS) using the proposed ALCA as an infrared counter countermeasure The simulation results show that the RSIS using our method is better than the conventional one in terms of the tracking performance.

• Nuclear Engineering and Technology
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• v.45 no.4
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• pp.529-538
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• 2013

Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1485-1490
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user, does face recognition and vital for many surveillance based systems. Advantage of face recognition when compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to decrease in dimension from of image acquisition step and various changes associated with face pose and background. Factors that deteriorate performance of face recognition are many such as distance from camera to face, lighting change, pose change, and change of facial expression. In this paper, we implement a new 3D active camera system to prevent various pose variation that influence face recognition performance and propose face recognition algorithm for intelligent surveillance system and mobile robot system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.1-9
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• 2011

This paper presents a novel scratch detection and removal approach for old film images in wavelet-domain. Various scratch detection and removal algorithms have been proposed for past decades. However, accurate scratch detection and removal with a moderate amount of computing effort is still a problem because of trade off between the quality of the film and computational load. For overcoming this problem, we first decompose an input image using a 3-level wavelet transform, and then remove the scratch by shrinking wavelet coefficients using linear interpolation. Experimental results show that the proposed algorithm can efficiently detect and remove the scratch in damaged films, and also be incorporated into old film restoration systems.

• Bulletin of the Korean Space Science Society
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• 2000.10a
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• pp.110-110
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• 2000

No Abstract, See Full Text

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.80-87
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• 2011

In this paper we present subject region-based auto-focusing algorithm using noise robust focus measure. The proposed algorithm automatically estimates the main subject using entropy and solves the traditional problems with a subject position or high frequency component of background image. We also propose a new focus measure by analyzing the discrete cosine transform coefficients. Experimental results show that the proposed method is more robust to Gaussian and impulse noises than the traditional methods. The proposed algorithm can be applied to Pan-tilt-zoom (PTZ) cameras in the intelligent video surveillance system.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1688-1691
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• 2007

This paper shows that the boundary image sticking can be prohibited completely by using the vacuum sealing process, which means that the residual impurities such as nitrogen or oxygen can be a critical factor inducing the boundary image sticking. The production of boundary image sticking was checked in the test panel fabricated by the $N_2$ or $O_2$ flow during the vacuum sealing process. As a result, the boundary image sticking did not appear in the case of $N_2flow$, whereas the boundary image sticking was observed in the case of $O_2$ flow even though the test panel was fabricated by the vacuum sealing process.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1291-1306
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• 2022

The dual image-based reversible data hiding scheme embeds secret data into two images to increase the embedding capacity of secret data. The dual image-based reversible data hiding scheme can transmit a lot of secret data. Therefore, various schemes have been proposed until recently. In 2021, Chen and Hong proposed a dual image-based reversible data hiding scheme that embeds a large amount of secret data using a reference matrix, secret data, and bit values. However, in this paper, more secret data can be embedded than Chen and Hong's scheme. To achieve this goal, the proposed scheme generates polynomials and shared values using secret sharing scheme, and embeds secret data using reference matrix and septenary number, and random value. Experimental results show that the proposed scheme can transmit more secret data to the receiver while maintaining the image quality similar to other dual image-based reversible data hiding schemes.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.204-207
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• 2002

The current paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm In the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3D-SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.1
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• pp.1-9
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• 2015

Template matching is used for many applications in image processing. One of the most researched topics is object tracking. Normalized Cross Correlation (NCC) is the basic statistical approach to match images. NCC is used for template matching or pattern recognition. A template can be considered from a reference image, and an image from a scene can be considered as a source image. The objective is to establish the correspondence between the reference and source images. The matching gives a measure of the degree of similarity between the image and the template. A problem with NCC is its high computational cost and occasional mismatching. To deal with this problem, this paper presents an algorithm based on the Sum of Squared Difference (SSD) and an adaptive template matching to enhance the quality of the template matching in object tracking. The SSD provides low computational cost, while the adaptive template matching increases the accuracy matching. The experimental results showed that the proposed algorithm is quite efficient for image matching. The effectiveness of this method is demonstrated by several situations in the results section.