• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.225-228
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• 2005

According to a popularization of the Internet and digital lifestyle, digital watermarks have been proposed for protection of copyrighted multimedia content. In blind watermark detection, which an original image is not provided, robustness against geometric distortion and compression remains challenging. In this paper, we propose a new perceptual blind discrete wavelet transform - discrete Fourier transform (DWT-DFT) composite watermarking scheme that is robust against both general linear transform and JPEG compression. This algorithm constructs an image-dependent watermark in the most significant DWT coefficients, which is determined by using a hierarchical tree structure. Strength of watermark is determined from a just-noticeable difference (JND) profile of a perceptual model. Furthermore, a desired template is inserted into DFT domain of the watermarked image. In new manner, a cross-ratio of four collinear points is used for detecting the template. Experimental results have showed that the proposed scheme is robust against general linear distortion, JPEG compression and various general kinds of attacks in the Stirmark 3.1 watermark evaluation tool.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.450-455
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• 2009

Amplitude-only logarithmic Radon transform (ALR transform) for pattern matching is proposed. This method provides robustness for object translation, scaling, and rotation. An ALR image is invariant even if objects are translated in a picture. For the object scaling and rotation, the ALR image is merely translated. The objects are identified using a phase-only matched filter to the ALR image. The ratio of size, the difference of rotation angle, and the position between the two objects are detected. Our pattern matching procedure is described, herein, and its simulation is executed. We compare matching scores with the Fourier-Mellin transform, and the general phase-only matched filter.

• Fibers and Polymers
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• v.6 no.2
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• pp.156-161
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• 2005

The gray line-profile method is introduced to find fabric density. Some patterned fabrics like stripe design as well as solid fabrics of basic weave structures are used to verify the efficiency and accuracy of the method. The approach is compared with Fourier transform method. Although the gray line-profile method is concise, it shows good results in both solid and patterned fabrics. In addition, it does not require a pre-processing or filtering technique in space or frequency domain to enhance the image suitable for the analysis. However, the approach is slightly influenced by the filter size for finding the local minimums of profile graph.

• Journal of the Optical Society of Korea
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• v.12 no.3
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• pp.136-146
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• 2008

We proposed an adaptive steganography of an optical image using bit-planes and multichannel characteristics. The experiment's purpose was to compare the most popular methods used in optical steganography and to examine their advantages and disadvantages. In this paper we describe two digital methods: the first uses less significant bits(LSB) to encode hidden data, and in the other all blocks of $n{\times}n$ pixels are coded by using DCT(Digital Cosine Transformation), and two optical methods: double phase encoding and digital hologram watermarking with double binary phase encoding by using IFTA(Iterative Fourier Transform Algorithm) with phase quantization. Therefore, we investigated the complexity on bit plane and data, similarity insert information into bit planes. As a result, the proposed method increased the insertion capacity and improved the optical image quality as compared to fixing threshold and variable length method.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.37-41
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• 1995

In this paper, we proposed the 2-stage ultrasound liver image classifier which uses the fractal dimensions obtained from the original image and its 1/2 subsampled image, and the Normalized Fourier Power Spectrum. The fractal dimension based on Fractional Brownian Motion (FBM) is calculated from the variance of the same scale pixels instead of the mean of them. Since the actual ultrasound. liver images does not fully match the FBM, to get the fractal dimension, we use the scale vectors which satisfy the FBM model. In 2-stage classifier, we first classified normal and diffuse liver and then classified the fat liver and cirrhosis from the diffuse liver. For the test liver images. 70% of normal liver and 80% of fat liver and 90% of cirrhosis is classified classified with our 2-stage classifier.

• Korean Journal of Optics and Photonics
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• v.16 no.4
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• pp.326-333
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• 2005

Phase-only encryption scheme using exclusive-OR rules in Fourier plane and a single path decryption system are presented. A zero-padded original image, multiplied by a random phase image, is Fourier transformed and its real-valued data is encrypted with key data by using XOR rules. A decryption is simply performed based on 2-1 setup with spatial filter by Fourier transform for multiplying phase-only encrypted data by phase-only key data, which are obtained by phase-encoding process, and spatial filtering for zero-order elimination in inverse-Fourier plane. Since the encryption process is peformed in Fourier plane, proposed encryption scheme is more tolerant to loss of key information by scratching or cutting than previous XOR encryption method in space domain. Compare with previous phase-visualization systems, due to the simple architecture without a reference wave, our system is basically robust to mechanical vibrations and fluctuations. Numerical simulations have confirmed the proposed technique as high-level encryption and simple decryption architecture.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.713-718
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• 1987

In this paper, an iterative restoration algorithm from power spectral density with 1 bit sign information of real part of two dimensional Fourier transform of image corrupted by additive white Gaussian noise is proposed. This method is a modified version of image reconstruction algorithm from power spectral density. From the results of computer simulation with original 32 gray level imgae of 64x64 pixels, we can find that restorated image after each iteration converge to original image very fast, and SNR gain be at least 8[dB] after 10th iteration for corrupted image with additive white Gaussian noise.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.3
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• pp.10-19
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• 2009

In this paper, an efficient optical watermark method using multiple phase wrapping and real-valued decoding key is proposed. In the embedding process, two zero-padded original images placed in two quadrants on input plane are multiplied with two statistically independent random phase patterns and are Fourier transformed, respectively. Two encoded images are obtained by taking the real-valued data from these Fourier transformed images. And then two phase-encoded patterns, used as a hidden image and a decoding key, are generated by the use of multiple phase wrapping from each of the encoded images. A transmitted image is made from the linear superposition of the weighted hidden images and a cover image. In reconstruction process, the mirror reconstructed images can be obtained at all quadrants by the inverse-Fourier transform of the product of the transmitted image and the decoding key. Computer simulation and optical experiment are demonstrated in order to confirm the proposed method.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.263-272
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• 2007

This paper proposes a skeleton-based hierarchical shape description scheme, called a skeleton tree, for accurate shape-based image retrieval. A skeleton tree represents an object shape as a hierarchical tree where high-level nodes describe parts of coarse trunk regions and low-level nodes describe fine details of boundary regions. Each node refines the shape of its parent node. Most of the noise disturbances are limited to bottom level nodes and the boundary noise is reduced by decreasing weights on the bottom levels. The similarity of two skeleton trees is computed by considering the best match of a skeleton tree to a sub-tree of another skeleton tree. The proposed method uses a hybrid similarity measure by employing both Fourier descriptors and moment invariants in computing the similarity of two skeleton trees. Several experimental results are presented demonstrating the validity of the skeleton tree scheme for the shape description and indexing.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.49-58
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• 2020

In this study, we solve an online multi-object problem which finds object states (i.e. locations and sizes) while conserving their identifications in online-provided images and detections. We handle this problem based on a tracking-by-detection approach by linking (or associating) detections between frames. For more accurate online association, we propose novel online appearance learning with discrete fourier transform and partial least square analysis (PLS). We first transform each object image into a Fourier image in order to extract meaningful features on a frequency domain. We then learn PLS subspaces which can discriminate frequency features of different objects. In addition, we incorporate the proposed appearance learning into the recent confidence-based association method, and extensively compare our methods with the state-of-the-art methods on MOT benchmark challenge datasets.