• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.62-76
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• 1994

In this paper, a segmentation-based coding technique as applied to video sequences is proposed. A proposed method separates an image into contour and texture parts, then the visually-sensitive contour part is represented by chain codes and the visually-insensitive texture part is reconstructed by a representative motion vector of a region and mean of the segmented frame difference. It uses a change detector to find moving areas and adopts variable blocks to represent different motions correctly. For better quality of reconstructed images, the displaced frame difference between the original image and the motion compensated image reconstructed by the representative motion vector is segmented. Computer simulation with several video sequences shows that the proposed method gives better performance than the conventional ones in terms of the peak signal to noise ratio(PSNR) and compression ration.

• Transactions on Electrical and Electronic Materials
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• v.18 no.6
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• pp.320-322
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• 2017

In this paper, a high-performance, low-area gradient-magnitude calculator architecture is proposed, based on approximate image processing. To reduce the computational complexity of the gradient-magnitude calculation, vector properties, the symmetry axis, and common terms were applied in a hardware-resource-shared architec-ture. The proposed gradient-magnitude calculator was implemented using an Altera Cyclone IV FPGA (EP4CE115F29) and the Quartus II v.16 device software. It satisfied the output-data quality while reducing the logic elements by 23% and the embedded multipliers by 76%, compared with previous work.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.5
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• pp.30-38
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• 1996

A PIV system consisting of an image board slit into personal computer and 2-D sheet light projector is developed and related techniques to improve its performance are discussed. A grey-level cross correlation method capable of overcoming particle seeding limitation is suggested. And a sub-pixed interpolation method in determining the vector terminal is preposed by considering 8-neighbours correlation distributing patterns. Furthermore, pressure estimation from the acquired velocity vectors by applying the Poisson equation is persented with reasonable feasibility. As a practical application of the present system, evaporator flows are analysed and attained instantaneous velocity vectors reveal that the flow phenomena maintain turbulent fluctuation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.61-68
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• 2002

This paper presents a new matching algorithm for fingerprint recognition, which is robust to image translation. The basic idea of this paper is to estimate the translation vector of an imput fingerprint image using N minutiae at which the gradient of the ridge direction field is large. Using the estimated translation vector we select minutiae irrelevant to the translation. We experimentally prove that the presented algorithm results in good performance even if there are large translation and pseudo-minutiae.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4624-4642
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• 2014

Image compression is a popular research issue that focuses on the problems of reducing the size of multimedia files. Vector Quantization (VQ) is a well-known lossy compression method which can significantly reduce the size of a digital image while maintaining acceptable visual quality. A locally adaptive scheme (LAS) was proposed to improve the compression rate of VQ in 1997. However, a LAS needs extra indicators to indicate the sources, consequently the compression rate of LAS will be affected. In this paper, we propose a novel method to eliminate the LAS indicators and so improve the compression rate. The proposed method uses the concept of data hiding to conceal the indicators, thus further improving the compression rate of LAS. From experimental results, it is clearly demonstrated that the proposed method can actually eliminate the extra indicators while successfully improving the compression rate of the LAS.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.1
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• pp.105-111
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• 1990

In this paper, fast algorithms to generate the codebook of vector quantization in image coding, are proposed. And an efficient algorithm to guess a initial codebook, namely, binary splitting method, is proposed. We generated the initial codebook by binary splitting method and then reduced the searching time using Iterative Optimization algorithm as an alternate to the generalized Lloyd algorithm and several information from binary splitting method. And the searching time and performance can be traded off by varying the searching range. With this proposed algorithm, the computation time can be reduced by a factor of 60 Without any degradation of image quality.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.119-124
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• 2024

Effective fire sensing is important to protect lives and property from the disaster. In this paper, we present an intelligent visual sensing method for detecting fires based on machine learning techniques. The proposed method involves a two-step process. In the first step, fire and non-fire images are used to train a convolutional neural network (CNN), and in the next step, feature vectors consisting of 256 values obtained from the CNN are used for the learning of a support vector machine (SVM). Linear and nonlinear SVMs with different parameters are intensively tested. We found that the proposed hybrid method using an SVM with a linear kernel effectively increased the recall rate of fire image detection without compromising detection accuracy when an imbalanced dataset was used for learning. This is a major contribution of this study because recall is important, particularly in the sensing of disaster situations such as fires. In our experiments, the proposed system exhibited an accuracy of 96.9% and a recall rate of 92.9% for test image data.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.159-167
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• 2006

Lipreading has been suggested as one of the methods to improve the performance of speech recognition in noisy environment. However, existing methods are developed and implemented only in software. This paper suggests a hardware design for real-time lipreading. For real-time processing and feasible implementation, we decompose the lipreading system into three parts; image acquisition module, feature vector extraction module, and recognition module. Image acquisition module capture input image by using CMOS image sensor. The feature vector extraction module extracts feature vector from the input image by using parallel block matching algorithm. The parallel block matching algorithm is coded and simulated for FPGA circuit. Recognition module uses HMM based recognition algorithm. The recognition algorithm is coded and simulated by using DSP chip. The simulation results show that a real-time lipreading system can be implemented in hardware.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.81-91
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• 1994

A DCT map and new cldebook design algorithm based on a two-dimension discrete cosine transform (2D-DCT) is presented for coder of image vector quantizer. We divide the image into smaller subblocks, then, using 2D DCT, separate it into blocks which are hard to code but it bears most of the visual information and easy to code but little visual information, and DCT map is made. According to this map, the significant features of training image are extracted by using the 2D DCT. A codebook is generated by partitioning the training set into a binary tree based on tree-structure. Each training vector at a nonterminal node of the binary tree is directed to one of the two descendants by comparing a single feature associated with that node to a threshold. Compared with the pairwise neighbor (PPN) and classified VQ(CVQ) algorithm, about 'Lenna' and 'Boat' image, the new algorithm results in a reduction in computation time and shows better picture quality with 0.45 dB and 0.33dB differences as to PNN, 0.05dB and 0.1dB differences as to CVQ respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.72-80
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• 2009

Look-up table based inverse halftoning from the digital color halftone image is proposed in this paper, which uses vector adaptive filter for the nonexisting patterns in the table. Halftone image is obtained from a continuous -tone image, which can be restored into continuous one from the digital binary image by way of inverse halftoning method. Look-up table based method usually processes fast and has even performances over the various halftoning. The numbers of pixels in the pattern of table and the method how to define the table elements for each R, G, B channels can effect largely for its performance. The proposed method uses 16 pixels in the table considering the diversity of the expressions from their patterns and with memory size as well. This also proposed how to combine R, G, B channels into one. Experimental results showed the better performance in the expression of colors, better color restoration and the short processing time compared with the conventional ones.