• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.599-608
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• 2013

Motion compensated interpolation (MCI) techniques are used for increasing the frame rate and generating the side information in the distributed video coding (DVC) system. In this paper, an efficient MCI technique using the image resizing in the DCT or LiftLT domain is proposed, and the performance of the MCI technique using various sub-pixel generation techniques is analyzed. Extensive computer simulations show that the proposed method produces the superior results compared to the conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2121-2128
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• 2015

In this paper presents a method of extracting reliable and regions of interest (ROI) in barcode for the purpose of factory automation. backgrounds are separated based on directional components and the characteristics of detected patterns. post-processing is performed on candidate images with analysis of problems caused by blur, rotation and areas of high similarity. In addition, the resizing factor is used to achieve faster calculations through image resizing. The input images contained multiple product or barcode for application to diverse automation environments; a high extraction success rate is accomplished despite the maximum shooting distance of 80 cm. Simulations involving images with various shooting distances gave an ROI detection rate of 100% and a post-processing success rate of 99.3%.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.9-15
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• 2021

It is a challenge for visually impaired people to access unfamiliar environments independently, hence the quality of life is reduced, and safety of life is compromised. An accurate and reliable door detection system comprising of way finding and indoor navigation can be beneficial for a large number of autonomous and mobile applications for visually impaired people. This paper illustrates an image-based door detection scheme for visually impaired people using stable features (edges and corners) including color averaging and image resizing. Simulation results show that the proposed scheme shows a significant improvement when compared with existing scheme.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1110-1113
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• 2012

Various image interpolation methods have been proposed to increase the resolution of images and accuracy of motion estimation of video, and the interpolation filters are used in H.264/AVC and HEVC standards. In this paper, we propose an efficient image interpolation method using lapped transforms. The relation between the resizing and interpolation of images is used in the proposed method, and the complexity is significantly reduced, while the performance of the proposed method is almost the same as conventional methods.

• Journal of IKEEE
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• v.23 no.4
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• pp.1415-1422
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• 2019

Background subtraction is the major task of computer vision and image processing to detect changes in video. The best performing background subtraction is computationally expensive that cannot be used in real time in a typical computing environment. The proposed algorithm improves the background subtraction algorithm of the widely used MOG with the image resizing algorithm. The proposed image resizing algorithm is designed to drastically reduce the amount of computation and to utilize local information, which is robust against noise such as camera movement. Experimental results of the proposed algorithm have a classification capability that is close to the state of the art background subtraction method and the processing speed is more than 10 times faster.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.4-49
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• 2001

Digit recognition based on backpropagation neural networks, as an important application of pattern recognition, was attracted much attention. Although it has the advantages of parallel calculation, high error-tolerance, and learning capability, better recognition effects can only be achieved with some specific fixed format input of the digit image. Therefore, digit image preprocessing ability directly affects the accuracy of recognition. Here using Matlab software, the digit image was enhanced by resizing and neutral-rotating the extracted digit image, which improved the digit recognition capability of the backpropagation neural network under practical conditions. This method may also be helpful for recognition of other patterns with backpropagation neural networks.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.100-106
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• 2015

In this paper, we propose a fast algorithm for low-power image enhancement method for mobile LCD. In the proposed fast algorithm, the spatial resolution of the input image is significantly reduced, and the image characteristics are analyzed on the reduced resolution image to find a dimming rate adaptive to the image content, thereby saving power. The proposed fast adaptive dimming and image enhancement algorithm is implemented as an application that runs on an Android device. Image quality evaluation and running time analysis experiments on the device indicate that the proposed fast algorithm jointly minimizes the quality degradation and power consumption, reducing the required computation load by over 95%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1484-1489
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• 2004

Given a video frame in terms of its 8${\times}$8 block-DCT coefncients, we wish to obtain a downsized or upsized version of this Dame also in terms of 8${\times}$8 block DCT coefficients. The DCT being a linear unitary transform is distributive over matrix multiplication. This fact has been used for downsampling video frames in the DCT domains in Dugad's, Mukherjee's, and Park's methods. The downsampling and upsampling schemes combined together preserve all the low-frequency DCT coefficients of the original image. This implies tremendous savings for coding the difference between the original frame (unsampled image) and its prediction (the upsampled image).This is desirable for many applications based on scalable encoding of video. In this paper, we extend the earlier works to various DCT sizes, when we downsample and then upsample of an image by a factor of two. Through experiment, we could improve the PSM values whenever we increase the DCT block size. However, because the complexity will be also increase, we can say there is a tradeoff. The experiment result would provide important data for developing fast algorithms of compressed-domain image/video resizing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.389-395
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• 2000

Digital Watermarking is a research area which aims at hiding secret information in digital multimedia content such as images, audio, and video. In this paper, we propose a new watermarking method with visually recognizable symbols into the digital images using wavelet transform, spread spectrum method and multilevel threshold value in considering the wavelet coefficients. The information of watermark can be extracted by subtracting wavelet coefficients with the original image and the watermarked image. The results of this experiment show that the proposed algorithm was superior to other similar watermarking algorithms. We showed Watermarking algorithm in JPEG lossy compression, resizing, LSB(Least Significant Bit) masking, and filtering.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.690-695
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• 2014

This paper presents a modified CCI image interpolation method based on the even-odd decomposition (EOD). The CCI method is a well-known technique to interpolate images. Although the method provides better image quality than the linear interpolation, its complexity still is a problem. To remedy the problem, this paper introduces analysis on the EOD decomposition of CCI and then proposes a reduced CCI interpolation in terms of complexity, providing better image quality in terms of PSNR. To evaluate the proposed method, we conduct experiments and complexity comparison. The results indicate that our method do not only outperforms the existing methods by up to 43% in terms of MSE but also requires low-complexity with 37% less computing time than the CCI method.