• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.403-413
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• 2011

In this paper, we proposed a digital image watermarking technique using scrambled binary phase computer generated hologram in the discrete cosine transform(DCT) domain. For the embedding process of watermark. Using simulated annealing algorithm, we would generate a binary phase computer generated hologram(BPCGH) which can reconstruct hidden image perfectly instead of hidden image and encrypt it through the scramble operation. We multiply the encrypted watermark by the weight function and embed it into the DC coefficients in the DCT domain of host image and an inverse DCT is performed. For the extracting process of watermark, we compare the DC coefficients of watermarked image and original host image in the DCT domain and dividing it by the weight function and decrypt it using descramble operation. And we recover the hidden image by inverse Fourier transforming the decrypted watermark. Finally, we compute the correlation between the original hidden image and recovered hidden image to determine if a watermark exits in the host image. The proposed watermarking technique use the hologram information of hidden image which consist of binary values and scramble encryption technique so it is very secure and robust to the various external attacks such as compression, noises and cropping. We confirmed the advantages of the proposed watermarking technique through the computer simulations.

• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.630-635
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• 2003

We propose an encryption method using visual cryptography and virtual phase images. In the encryption process, the original image is shared by virtual images and the decryption key image. We multiply the virtual phase images with each complex image, which has the constant value of its sum after performing the phase modulation of the virtual images and the decryption key. The encryption cards are made by Fourier transforming the multiplied images. It is possible to protect information about the original image because the cards do not have any information from the original image. To reconstruct the original image, all the encryption cards are placed on each path of a Mach-Zehnder interferometer and then the lights passing through them are summed. Since the summed image is inverse Fourier transformed by a Fourier lens, the phase image is multiplied with the decryption key and the output image is obtained in the form of intensity on the CCD plane. Computer simulations show a good performance of the pro-posed optical security system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.159-164
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• 2004

In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simultaneous perturbation method as an image reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.251-256
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• 1993

In KACC'91 and '92 conference, we proposed a method of automatically detecting the shape of the faulty holes in a shadow mask by use of CCD ca.mera and image data processing technic. In this method, two adjoining test areas from one image data. of the shadow mask are taken and comparing the shape of holes in these two areas, we can detect the faults in the shadow mask. In this paper, a method is described by use of spatial filtering of effectively finding the faulty holes from the difference image data between the two tested image data. The main role of the filter is to remove sampling errors occurring at the edge of the holes. And the second role is not only to find the existence of faulty holes but also exactly express the shape of faulty holes. Computer simulations and actual experiments with shadow masks have shown that this method of fault detection is very effective for practical use.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.745-749
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• 1998

Mathematical morphology (MM) has been introduced as a powerful tool for studying the geometrical properties of images, MM is a good approach to digital image processing , which is based on the shape feature. The MM operators such as dilation, erosion, closing and opening have been applied successfully to image noise reduction. The MM filters can easily filter the noise when the noise factors are known. However it is very difficult to reduce the noise when images are ambiguous, because the boundary between the noise and object is vague. In this paper, we propose a new method to reduce noise from ambiguous images by using Fuzzy Mathematical Morphology (FMM) operators. Performance evaluation via simulations show that the FMM filters efficiently reduce the image noise. Furthermore, the FMM filters show a good performance compared with the conventional filters.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.478-481
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• 1999

In this paper, we could analyze and compare with the generalized Recurrent neural networks and the Recurrent neural networks applying the fuzzy. The total system is digitalized in order to be filtering the image, and the fuzzy is applied to the generalized Recurrent in order to be fast the operation speed. So the fuzzified Recurrent neural networks are completely removed to the included noise in the image, and could converge on a certain value as controlling the weight and iteration frequency corresponding to the desired target value. Also, that values are compared and analysed using MSE and PSNR. When applying to the image which is included to the noise in the generalized Recurrent and the Recurrent applying the fuzzy, the Recurrent applying the fuzzy is shown the superiority at the noise and the fixed convergence part through MSE and PSNR in the computer simulations.

• Current Optics and Photonics
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• v.3 no.4
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• pp.320-328
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• 2019

A method for joint-transform correlator (JTC) multiple-image encryption based on a quick-response (QR) code key is proposed. The QR codes converted from different texts are used as key masks to encrypt and decrypt multiple images. Not only can Chinese text and English text be used as key text, but also symbols can be used. With this method, users have no need to transmit the whole key mask; they only need to transmit the text that is used to generate the key. The correlation coefficient is introduced to evaluate the decryption performance of our proposed cryptosystem, and we explore the sensitivity of the key mask and the capability for multiple-image encryption. Robustness analysis is also conducted in this paper. Computer simulations and experimental results verify the correctness of this method.

• International Journal of Automotive Technology
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• v.6 no.1
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• pp.53-63
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• 2005

We propose a fuzzy neural network (FNN) theory capable of deciding the quality of a road image prior to extracting lane-related information. The accuracy of lane-related information obtained by image processing depends on the quality of the raw images, which can be classified as good or bad according to how visible the lane marks on the images are. Enhancing the accuracy of the information by an image-processing algorithm is limited due to noise corruption which makes image processing difficult. The FNN, on the other hand, decides whether road images are good or bad with respect to the degree of noise corruption. A cumulative distribution function (CDF), a function of edge histogram, is utilized to extract input parameters from the FNN according to the fact that the shape of the CDF is deeply correlated to the road image quality. A suitability analysis shows that this deep correlation exists between the parameters and the image quality. The input pattern vector of the FNN consists of nine parameters in which eight parameters are from the CDF and one is from the intensity distribution of raw images. Experimental results showed that the proposed FNN system was quite successful. We carried out simulations with real images taken in various lighting and weather conditions, and obtained successful decision-making about $99\%$ of the time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2415-2423
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• 1999

We propose a new optical method which conceals the data of authorized persons by encryption before they are stored or compared in the pattern recognition system for security systems. This proposed security system is made up of two subsystems : a proposed optical encryption system and a pattern recognition system based on the JTC which has been shown to perform well. In this system, each image of authorized persons as a reference image is stored in memory units through the proposed encryption system. And if a fingerprint image is placed in the input plane of this security system for access to a restricted area, the image is encoded by the encryption system then compared with the encrypted reference image. Therefore because the captured input image and the reference data are encrypted, it is difficult to decrypt the image if one does not know the encryption key bit stream. The basic idea is that the input image is encrypted by performing optical XOR operations with the key bit stream that is generated by digital encryption algorithms. The optical XOR operations between the key bit stream and the input image are performed by the polarization encoding method using the polarization characteristics of LCDs. The results of XOR operations which are detected by a CCD camera should be used as an input to the JTC for comparison with a data base. We have verified the idea proposed here with computer simulations and the simulation results were also shown.

• Journal of the Korea Computer Industry Society
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• v.5 no.5
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• pp.737-746
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• 2004

Two-channel multiwavelet system is investigated for image compression application in this paper. Generally, multiwavelets are known for their superb capability of compressing non-stationary signals like voice. However, multivavelet system have a critical problem in processing and compressing image data due to mesh-grid visual artifacts. In our two-channel multiwavelet system we have investigated incorporation of pre and post filtering to the multiwavelet transform and compression system for alleviating those ingerent visual artifacts due to multiwavelet effect. In addition, to quantify the image data compression performance of proposed multiwavelet system, computer simulations have been performed using various image data. For bit allocation and quantization, the Lagrange multiplier technique considering data rate vs. distortion rate along with a nonlinear companding method are applied equallly to all systems considered, here. The simulation results have yielded 1 ~ 2 dB compression enhancement over the scalar savelet systems. If the more advanced compression methods like SPIHT and run-length channel coding were adopted for the proposed multiwavelet system, a much higher compression gain could be obtained.