• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4567-4587
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• 2017

With the growth of the Internet and the extensive applications of image editing software, it has become easier to manipulate digital images without leaving obvious traces. Copy-move is one of the most common techniques for image forgery. Image blind forensics is an effective technique for detecting tampered images. This paper proposes an improved copy-move forgery detection method based on the discrete cosine transform (DCT). The quantized DCT coefficients, which are feature representations of image blocks, are truncated using a truncation factor to reduce the feature dimensions. A method for judging whether two image blocks are similar is proposed to improve the accuracy of similarity judgments. The main transfer vectors whose frequencies exceed a threshold are found to locate the copied and pasted regions in forged images. Several experiments are conducted to test the practicability of the proposed algorithm using images from copy-move databases and to evaluate its robustness against post-processing methods such as additive white Gaussian noise (AWGN), Gaussian blurring, and JPEG compression. The results of experiments show that the proposed scheme effectively detects both copied region and pasted region of forged images and that it is robust to the post-processing methods mentioned above.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.4
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• pp.361-372
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• 2010

Optical image stabilization is a technique to compensate the image blurring caused by some vibrations of camera at the exposure time. Pitching and yawing of camera are sensitive to the image quality so they are usually compensated by optical image stabilization. Corresponding pitching and yawing of a camera, a lens or the image sensor is translated in two-axis direction and then the optical path of camera is adjusted. In this paper, two-axis OIS actuator for mobile camera module is suggested and designed. The actuator is a voice-coil actuator that uses the electromagnetic force of voice-coil to make compensation motions. And ball bearing is used to reduce friction force. Magnetic attractive force between magnets and yokes acts as a preload and magnet springs. Prototype actuator is fabricated to measure the friction force and to verify the feasibility of the OIS actuator with ball bearing. At last, the actuator is improved in consideration of driving force and friction force. Design of experiments is used for designing the actuator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.855-870
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• 2019

In this paper, an adaptive iterative algorithm is proposed for motion deblurring by using the salient intensity prior. Based on the observation that the salient intensity of the clear image is sparse, and the salient intensity of the blurred image is less sparse during the image blurring process. The salient intensity prior is proposed to enforce the sparsity of the distribution of the saliency in the latent image, which guides the blind deblurring in various scenarios. Furthermore, an adaptive iteration strategy is proposed to adjust the number of iterations by evaluating the performance of the latent image and the similarity of the estimated blur kernel. The negative influence of overabundant iterations in each scale is effectively restrained in this way. Experiments on publicly available image deblurring datasets demonstrate that the proposed algorithm achieves state-of-the-art deblurring results with small computational costs.

• Journal of IKEEE
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• v.25 no.1
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• pp.139-147
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• 2021

This paper introduces an image decomposition-based deep learning method and loss function to improve low-light images. In order to remove color distortion and halo artifact, illuminance channel of an input image is decomposed into reflectance and luminance channels, and a decomposition-based multiple structural deep learning process is applied to each channel. In addition, a mixed norm-based loss function is described to increase the stability and remove blurring in reconstructed image. Experimental results show that the proposed method effectively improve various low-light images.

• Progress in Medical Physics
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• v.19 no.3
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• pp.150-156
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• 2008

An applied technique of contrast enhancement for X-ray image is proposed which is based on combined enhancement of scaling and wavelet coefficients in discrete wavelet transform space. Conventional contrast enhancement methods such as contrast limited adaptive histogram equalization (CLAHE), multi-scale image contrast amplification (MUSICA) and gamma correction were applied on scaling coefficients to enhance the contrast of an original. In order to enhance the detail as well as reduce the blurring caused by up scaling of contrast modified scale coefficients from lower resolution, the sigmoid manipulation function was used to manipulate wavelet coefficients. The contrast detail mammography (CDMAM) phantom was imaged and processed to measure the image line profile of results and contrast to noise ratio (CNR) comparatively. The proposed technique produced better results than direct application of various contrast enhancement methods on image itself. The proposed method can enhance contrast, and also suppress the amplification of noise components in a single process. It could be useful for various applications in medical, industrial and graphical images where contrast and detail are of importance.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.249-255
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• 2013

In this paper, we propose an algorithm to detect scale invariant object from IR image obtained in the sea environment. We create horizontal edge (HL), vertical edge (LH), diagonal edge (HH) of images through 2-D discrete Haar wavelet transform (DHWT) technique after noise reduction using morphology operations. Considering the sea environment, Gaussian blurring to the horizontal and vertical edge images at each level of wavelet is performed and then saliency map is generated by multiplying the blurred horizontal and vertical edges and combining into one image. Then we extract object candidate region by performing a binarization to saliency map. A small area in the object candidate region are removed to produce final result. Experiment results show the feasibility of the proposed algorithm.

• Fashion & Textile Research Journal
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• v.15 no.6
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• pp.874-885
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• 2013

This study analyzes the visage in fashion illustration based on the deconstructed visage of Francis Bacon's paintings as well as analyzes fashion illustration works since 2000. The deconstructed visages in Francis Bacon's paintings are classified as blurring, elimination, distortion and division. The expressive methods and meanings in fashion illustration (according to categorization) are as follow. Blurring shows an ambiguous visage organ by the sweeping of the brush, removal of a boundary among the visage, body and clothes, gradation of organic line like visage shapes, stretching of the a plat combined to visage and fragmentation of visage. It represents an uncertainty of the fashion theme and image interpretation, impossibility of figure by ambiguity, fantastic effect and the induction of the uncanny. Elimination shows the background color's painting of a photo-montage, overlap of a cutting of visage's part and background of a plat, elimination of the visage and the elimination of eyes, nose or lips. It represents a weakened identity, the reinforcement of anonymity, creation of a violent image, and uncanny unfamiliarity. Distortion shows a distorted visage by free drawing, and unconscious drawing line, fluid digital body, combination of an unconscious curve, and an eccentric combination of the accidental. It represents the relief of specialty about realistic existence, hypothetical immateriality and fantasy. Division shows overlapped visages with different angles, the weird combination of a plural visage and different species and a plural breakaway of direction, and the position of several organs. It represents motion by power's trace, non-territory of species, ambiguity and uncertainty and the uncanny.

• Journal of Broadcast Engineering
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• v.9 no.2
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• pp.131-141
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• 2004

Current binocular stereoscopic displays cause visual discomfort when objects with large disparities are present in the scene. One solution for improving visual comfort is synthetic depth-of-field processing, which simulates the characteristics of a human visual system. With this technique, visual comfort is improved by blurring portions of the background and/or foreground in the scene. However, this technique has the drawback of degrading overall image quality because the blurring is typically applied to both left and right images. To alleviate the visual discomfort, we propose a novel disparity-based asymmetrical filtering technique. Proposed technique applies the filtering to the image of one eye only, and controls the blur level according to the disparity information between stereoscopic images. We investigate the effects of this technique on stereoscopic video by measuring visual comfort and apparent sharpness. Our results indicate that disparity-based asymmetrical filtering can improve visual comfort of stereoscopic video while it maintains apparent sharpness if unfixated regions with large disparities are blurred under the appropriate filtering condition.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.487-494
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• 2013

Medical image watermarking has received extensive attention as wide security services in the healthcare information system. This paper proposes a blind medical image watermarking approach on the segmented gray-matter (GM) images by utilizing discrete wavelet transform (DWT) and discrete cosine transform (DCT) along with enhanced suppressed fuzzy C-means (EnSFCM) for the optimal selection of sub-blocks position to insert a watermark. Experimental results show that the proposed approach outperforms other methods in terms of peak signal to noise ratio (PSNR) and M-SVD. In addition, the proposed approach shows better robustness than other methods in normalized correlation (NC) values against several attacks, such as noise addition, filtering, JPEG compression, blurring, histogram equalization, and cropping.