• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.309-317
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• 2022

In this paper, we propose a machine learning-based copy-move forgery detection network with dual branches. Because the rotation or scaling operation is frequently involved in copy-move forger, the conventional convolutional neural network is not effectively applied in detecting copy-move tampering. Therefore, we divide the input into rotation-invariant and scaling-invariant features based on the wavelet coefficients. Each of the features is input to different branches having the same structure, and is fused in the combination module. Each branch comprises feature extraction, correlation, and mask decoder modules. In the proposed network, VGG16 is used for the feature extraction module. To check similarity of features generated by the feature extraction module, the conventional correlation module used. Finally, the mask decoder model is applied to develop a pixel-level localization map. We perform experiments on test dataset and compare the proposed method with state-of-the-art tampering localization methods. The results demonstrate that the proposed scheme outperforms the existing approaches.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.19-28
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• 2023

This paper describes the experimental investigation of steel pallet rack beam-to-column connec-tions. Total behavior of moment-rotation (M-φ) curve and the effect of particular characteristics on the behavior of connection were studied and the associated load strain relationship and corre-sponding failure modes are presented. In this respect, an estimation of SPRBCCs moment and rotation are highly recommended in early stages of design and construction. In this study, a new approach based on Support Vector Machines (SVMs) coupled with discrete wavelet transform (DWT) is designed and adapted to estimate SPRBCCs moment and rotation according to four input parameters (column thickness, depth of connector and load, beam depth,). Results of SVM-WAVELET model was compared with genetic programming (GP) and artificial neural networks (ANNs) models. Following the results, SVM-WAVELET algorithm is helpful in order to enhance the accuracy compared to GP and ANN. It was conclusively observed that application of SVM-WAVELET is especially promising as an alternative approach to estimate the SPRBCCs moment and rotation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1095-1100
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• 2008

In a process of insect foot recognition, footprint segments as basic areas for recognition need to be extracted from scanned insect footprints and appropriate features should be found from the footprint segments in order to discriminate kinds of insects, because the characteristics of the features are important to classify insects. In this paper, we propose methods for automatic footprint segmentation and feature extraction. We use a Trace transform method in order to find out appropriate features from the extracted segments by the above methods. The Trace transform method builds a new type of data structure from the segmented images by functions using parallel trace lines and the new type of data structure has characteristics invariant to translation, rotation and reflection of images. This data structure is converted to Triple features by Diametric and Circus functions, and the Triple features are used for discriminating patterns of insect footprints. In this paper, we show that the Triple features found by the proposed methods are enough distinguishable and appropriate for classifying kinds of insects.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.459-464
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• 2003

This paper proposes the use of a wavelet based image transform algorithm in human iris recognition method and the effectiveness of this technique will be determined in preprocessing of extracting Iris image from the user´s eye obtained by imaging device such as CCD Camera or due to torsional rotation of the eye, and it also resolves the problem caused by invariant under translations and dilations due to tilt of the head. This technique values through the proposed translation-invariant wavelet transform algorithm rather than the conventional wavelet transform method. Therefore we extracted the best-matching iris feature values and compared the stored feature codes with the incoming data to identify the user. As result of our experimentation, this technique demonstrate the significant advantage over verification when it compares with other general types of wavelet algorithm in the measure of FAR & FRR.

• Current Optics and Photonics
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• v.2 no.4
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• pp.368-377
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• 2018

In this paper, we evaluate cryptographic properties of a double random phase encoding (DRPE) scheme in the discrete Gyrator domain with avalanche and bit independence criterions. DRPE in the discrete Gyrator domain is reported to have higher security than traditional DRPE in the Fourier domain because the rotation angle involved in the Gyrator transform is viewed as additional secret keys. However, our numerical experimental results demonstrate that the DRPE in the discrete Gyrator domain has an excellent bit independence feature but does not possess a good avalanche effect property and hence needs to be improved to satisfy with acceptable avalanche effect that would be robust against statistical-based cryptanalysis. We compare our results with the avalanche and bit independence criterion (BIC) performances of the conventional DRPE scheme, and improve the avalanche effect of DRPE in the discrete Gyrator domain by integrating a photon counting imaging technique. Although the Gyrator transform-based image cryptosystem has been studied, to the best of our knowledge, this is the first report on a cryptographic evaluation of discrete Gyrator transform with avalanche and bit independence criterions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1785-1791
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• 2003

This paper presents the mosaic method that the video sequence with shift and rotation information after Mellin Transform. The results are used to compute the projection matrix for each image registration. So before registration, we process camera calibration in order to reduce the image warp by camera and then compute the global projection matrix for image registration for reducing errors from rut image to last image. This paper describes the mosaic method that compute duplication and movement information quickly and robust noise using projection matrix on Mellin Transform.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.1136-1142
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• 1999

A difficulty of the visual inspection for translated, magnified and rotated objects exists owing to the limitation of recognition rate. In this paper, we perform to define Integral Logarithm Transform(ILT), to consider its characteristic for implementation of Translation-, Magnification- and Rotation-invariant inspection system, and to compare with other methods in inspection error rate. By using magnification and rotation invariance properties of ILT, it makes easier than other methods to extract the rotation degree. The new method employs the ILT for the good/bad inspection of translated, magnified and rotated objects and experiment is performed to achieve translation, magnification and rotation invariance. In other methods both magnification and rotation invariance can't be available. As the result of he experiment, it is not better than the self-organizing map in the improvement of recognition rate, but it shows us the possibility to be used as a tool for the good/bad inspection system.

• Convergence Security Journal
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• v.17 no.3
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• pp.21-29
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• 2017

Accurate encoding of local patterns is a very important factor in texture classification. However, LBP based methods w idely studied have fundamental problems that are vulnerable to noise. Recently, LDP method using edge response and dire ction information was proposed in facial expression recognition. LDP is more robust to noise than LBP and can accommod ate more information in it's pattern code, but it has drawbacks that it is sensitive to rotation transforms that are critical to texture classification. In this paper, we propose a new local pattern coding method called Rotation Invariant Local Direc tional Pattern, which combines rotation-invariant transform to LDP. To prove the texture classification performance of the proposed method in this paper, texture classification was performed on the widely used UIUC and CUReT datasets. As a result, the proposed RILDP method showed better performance than the existing methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.94-104
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• 2007

Iris recognition is biometric technology which uses a unique iris pattern of user in order to identify person. In the captured iris image by conventional iris recognition camera, it is often the case with eyelid occlusion, which covers iris information. The eyelids are unnecessary information that causes bad recognition performance, so this paper proposes robust algorithm in order to detect eyelid. This research has following three advantages compared to previous works. First, we remove the detected eyelash and specular reflection by linear interpolation method because they act as noise factors when locating eyelid. Second, we detect the candidate points of eyelid by using mask in limited eyelid searching area, which is determined by searching the cross position of eyelid and the outer boundary of iris. And our proposed algorithm detects eyelid by using parabolic hough transform based on the detected candidate points. Third, there have been many researches to detect eyelid, but they did not consider the rotation of eyelid in an iris image. Whereas, we consider the rotation factor in parabolic hough transform to overcome such problem. We tested our algorithm with CASIA Database. As the experimental results, the detection accuracy were 90.82% and 96.47% in case of detecting upper and lower eyelid, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.712-719
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• 2008

Temporal error concealment indicates the algorithm that restores the lost video data using temporal correlation between previous frame and current frame with lost data. It can be categorized into the methods of block-based and pixel-based concealment. The proposed method in this paper is for pixel-based temporal error concealment using affine transform. It outperforms especially when the object or background in lost block has geometric transform which can be modeled using affine transform, that is, rotation, magnification, reduction, etc. Furthermore, in order to maintain good performance even though one or more motion vector represents the motion of different objects, we defines a cost function. According to cost from the cost function, the proposed method adopts affine error concealment adaptively. Simulation results show that the proposed method yields better performance up to 1.9 dB than the method embedded in reference software of H.264/AVC.