• Bulletin of the Korean Mathematical Society
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• v.60 no.6
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• pp.1705-1714
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• 2023

We explicitly construct the smooth toric Fano variety which is isomorphic to the blow-up of the projective space at torus invariant points in codimension one by anti-flips.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.341-351
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• 2003

Digital image watermarking is the method that can protect the copyright of the image by embedding copyright information, which is called watermark. Watermarking must have robustness to intentional or unintentional data changing, called attack. The conventional watermarking schemes are robust to waveform attacks such as image compression, filtering etc. However, they are vulnerable to geometrical attacks such as rotation, scaling, translation, and cropping. Accordingly, this paper proposes new watermarking scheme that is robust to geometrical attacks by using invariant centroid. Invariant centroid is the gravity center of a central area in a gray scale image that remains unchanged even when the image is attacked by RST including cropping and proposed scheme uses invariant centroids of original and inverted image as the template. To make geometrically invariant domain, template and angle compensated Log -Polar Map(LPM) is used. Then Discrete Cosine Transform(DCT) is performed and the watermark is embedded into the DCT coefficients. Futhermore, to prevent a watermarked image from degrading due to interpolation during coordinate system conversion, only the image of the watermark signal is extracted and added to the original image. Experimental results show that the proposed scheme is especially robust to RST attacks including cropping.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.325-336
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• 2020

Nonlinear Invariant Attack is an attack that should be considered when constructing lightweight block ciphers with relatively simple key schedule. A shortcut to prove a block cipher's resistance against nonlinear invariant attack is checking the smallest dimension of linear layer-invariant linear subspace which contains all known differences between round keys is equal to the block size. In this paper, we presents the following results. We identify the structure and number of optimal bit-permutations which require only one known difference between round keys for a designer to show that the corresponding block cipher is resistant against nonlinear invariant attack. Moreover, we show that PRESENT-like block ciphers need at least two known differences between round keys by checking all PRESENT-like bit-permutations. Additionally, we verify that the variants of PRESENT-like bit-permutations requiring the only two known differences between round keys do not conflict with the resistance against differential attack by comparing the best differential trails. Finally, through the distribution of the invariant factors of all bit-permutations that maintain BOGI logic with GIFT S-box, GIFT-variant block ciphers require at least 8 known differences between round keys for the resistance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.9
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• pp.14-22
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• 2015

TIn this paper, a centering method for an unfocused input character using the spherical domain system and the centering character to use the shift invariant feature for the recognition system is proposed. A system for recognition is implemented using the centroid method with coordinate average values, and the results of an above 78.14% average differential ratio for the character features were obtained. It is possible to extract the shift invariant feature using spherical transformation similar to the human eyeball. The proposed method, which is feature extraction using spherical coordinate transform and transformed extracted data, makes it possible to move the character to the center position of the input plane. Both digital and optical technologies are mixed using a spherical coordinate similar to the 3 dimensional human eyeball for the 2 dimensional plane format. In this paper, a centering character feature using the spherical domain is proposed for character recognition, and possibilities for the recognized possible character shape as well as calculating the differential ratio of the centered character using a centroid method are suggested.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.454-460
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• 2000

To retrieve complex data such as images, the content-based retrieval method rather than keyword based method is required. In this paper, we implemented a content-based image retrieval system which retrieves object of user query effectively using invariant moments which have invariant properties about linear transformation like position transition, rotation and scaling. To extract the shape feature of objects in an image, we propose a labeling algorithm that extracts objects from an image and apply invariant moments to each object. Hashing method is also applied to reduce a retrieval time and index images effectively. The experimental results demonstrate the high retrieval efficiency i.e precision 85%, recall 23%. Consequently, our retrieval system shows better performance than the conventional system that cannot express the shale of objects exactly.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3063-3068
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• 1997

In this paper, we have extended the generalization back-propagation algorithm to multi-layer polynomial higher order neural networks. The purpose of this paper is to describe various pattern recognition using polynomial higher-order neural network. And we have applied shift position T-C test pattern for invariant pattern recognition and measured generalization by mirror symmetry problem. simulation result shows that the ability for invariant pattern recognition increase with the proposed technique. Recognition rate of invariant T-C pattern is 90% effective and of mirror symmetry problem is 70% effective when the proposed technique is utilized. These results are much better than those by the conventional methods.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.151-157
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• 1998

Free-space optical interconnection networks can be classified into two types, space variant and space invariant, according to the degree of space variance. In terms of physical implementations, the degree of space variance can be interpreted as the degree of sharing beam steering optics among the nodes of a given network. This implies that all nodes in a totally space-invariant network can share a single beam steering optics to realize the given network topology, whereas, in a totally space variant network, each node requires a distinct beam steering optics. However, space invariant networks require mechanisms for distinguishing the origins of incoming signals detected at the node since several signals may arrive at the same time if the node degree of the network is greater than one. This paper presents a signal source encoding scheme for distinguishing incoming signals efficiently, in terms of the number of detectors at each node or the number of unique wavelengths. The proposed scheme is solved by developing a new parallel genetic algorithm called distributed asynchronous genetic algorithm (DAGA). Using the DAGA, we solved signal distinction schemes for various network sizes of several topologies such as hypercube, the mesh, and the de Brujin.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.231-238
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• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.

• Communications of the Korean Mathematical Society
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• v.15 no.4
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• pp.649-668
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• 2000

In this paper we prove the following : Let M be a real (2n-1)-dimensional compact minimal semi-invariant submanifold in a complex projective space P(sub)n+1C. If the scalar curvature $\geq$2(n-1)(2n+1), then m is a homogeneous type $A_1$ or $A_2$. Next suppose that the third fundamental form n satisfies dn = 2$\theta\omega$ for a certain scalar $\theta$$\neq$c/2 and $\theta$$\neq$c/4 (4n-1)/(2n-1), where $\omega$(X,Y) = g(X,øY) for any vectors X and Y on a semi-invariant submanifold of codimension 3 in a complex space form M(sub)n+1 (c). Then we prove that M has constant principal curvatures corresponding the shape operator in the direction of the distingusihed normal and the structure vector ξ is an eigenvector of A if and only if M is locally congruent to a homogeneous minimal real hypersurface of M(sub)n (c).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1253-1272
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• 2010

In this paper, we propose a new affine shape adaptation scheme for the affine invariant feature detector, in which the convergence stability is still an opening problem. This paper examines the relation between the integration scale matrix of next iteration and the current second moment matrix and finds that the convergence stability of the method can be improved by adjusting the relation between the two matrices instead of keeping them always proportional as proposed by previous methods. By estimating and updating the shape of the integration kernel and differentiation kernel in each iteration based on the anisotropy of the current second moment matrix, we propose a coarse-to-fine affine shape adaptation scheme which is able to adjust the pace of convergence and enable the process to converge smoothly. The feature matching experiments demonstrate that the proposed approach obtains an improvement in convergence ratio and repeatability compared with the current schemes with relatively fixed integration kernel.