• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.434-440
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• 2003

Since Jacquine introduced the image coding algorithm using fractal theory, many fractal image compression algorithms providing good quality at low bit rate have been proposed by Fisher and Beaumount et al.. But a problem of the previous implementations is that the decoding rests on an iterative procedure whose complexity is image-dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and an input image to be encoded. As the decoding process can be completed with received fractal coefficients and predefined initial image without repeated iterations, the decoding time could be remarkably reduced.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.41-47
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• 2002

Fractal image compression can reduce the size of image data by the contractive mapping that is affine transformation to find the block(called as range block) which is the most similar to the original image. Even though fractal image compression is regarded as an efficient way to reduce the data size, it has high distortion rate and requires long encoding time. In this paper, we presented a hybrid fractal image compression system with the modified SOFM Vector Quantizer which uses improved competitive learning method. The simulation results showed that the VQ hybrid fractal using improved competitive loaming SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.328-332
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• 2003

Since Jacquine introduced the image coding algorithm using fractal theory, many fractal image compression algorithms providing good quality at low bit rate have been proposed by Fisher and Beaumount et al.. But a problem of the previous implementations is that the decoding rests on an iterative procedure whose complexity is image -dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and a input image to be encoded. As the decoding process can be completed with received fractal coefficients and predefined initial image without repeated iterations, the decoding time could be remarkably reduced.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.457-458
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• 2002

The fractal dimension is the characteristics that can quantitatively define the irregularity in natural. It is useful in describing the morphology or various rubbed surface for hydraulic piston motor instead of the stylus profiling method. But fractal parameters had not constructed on the morphological characteristic or rubbed surface because of the insufficient knowledge about a conception of fractal dimension. In this study, for the purpose or applying fractal I parameters practically, we have suggested way to establish the morphological characteristic of rubbed surface with fractal parameters, and we carried out an experiment on the lubricant friction and wear by using Ball-ON-Disk type tester. Materials were the brass and the bronze which are used to slipper-pad in the hydraulic piston motor. We searched for fractal parameters or surface structure with the digital image processing, Surface fractal dimension can be determined by sum of intensity difference of surface pixel. Using the image processing and fractal parameters for rubbed surface in the friction and wear test, morphology of rubbed sur race can be effectively obtained by fractal dimensions.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.623-626
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• 1999

As the information society is advanced, the needs for mass information storage and retrieval grows. Digital image information is stored in retrieval systems, broadcasting in television transmission and exchanged over several kinds of telecommunication media. A major problem is that digital images are represented with large amount of data. The useful feature of image compression is that transmitting rapidly a lot of data in less time. Therefore we proposed a parallel Fractal trans-formation unit in Fractal Image compression system.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.234-332
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• 2001

For a method improving fractal image segmentation which is a new application of fractal image coding, YST scheme have proposed an image segmentation scheme using labeling based on periodic points of pixel transformation and error-correction of labels by iterating fractal transformation. The scheme generates the high quality segmentation, however, it has the redundancy in the process of labeling and correction of labels. To solve this problem, we propose a labeling algorithm based on orbit of pixel transformation and restricted condition on iterating process of fractal transformation.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.559-566
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• 2012

In this paper, we propose a fast fractal image coding algorithm to shorten long time to take on fractal image encoding. For its performance evaluation, the algorithm compares with other traditional fractal coding methods. In the traditional fractal image coding methods, an original image is contracted by a factor in order to make the corresponding image to be compared with. Then, the whole area of the contracted image is searched in order to find the fixed point of contractive transformation of the original image corresponding to the contracted image. It needs a lot of searching time on encoding. However, the proposed algorithm considerably reduces encoding time by using scaling method and limited search area method. On comparison of the proposed algorithm with Jacquin's method, the proposed algorithm is dozens of times as fast as that of Jacquin's method on encoding time with a little degradation of the decoded image quality and a little increase of the compression rate. Therefore, it is found that the proposed algorithm largely improves the performance in the aspect of encoding time when compared with other fractal image coding methods.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.195-198
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• 2000

Fractal image compression can reduce the size of image data by contractive mapping of original image. The mapping is affine transformation to find the block(called range block) which is the most similar to the original image. Fractal is very efficient way to reduce the data size. However, it has high distortion rate and requires long encoding time. In this paper, we present the simulation result of fractal and VQ hybrid systems which use different clustering algorithms, normal and improved competitive learning SOFM. The simulation results showed that the VQ hybrid fractal using improved competitive learning SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.81-84
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• 2000

Fractal image compression can reduce the size of image data by contractive mapping of original image. The mapping is affine transformation to find the block(called range block) which is the most similar to the original image. Fractal is very efficient way to reduce the data size. However, it has high distortion rate and requires long encoding time. In this paper, we present the simulation result of fractal and VQ hybrid systems which use different clustering algorithms, normal and improved competitive learning SOFM. The simulation results showed that the VQ hybrid fractal using improved competitive learning SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• Imaging Science in Dentistry
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• v.35 no.1
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• pp.33-40
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• 2005

Purpose : (1) To analyse the effect of exposure time, ROI size and one impact factor in the image processing procedure on estimates of fractal dimension; and (2) to analyse the correlated relationship between the fractal dimension and the Cu-Eq value (bone density). Materials and Methods : The cylindric bone phantoms of 6 large and 5 small diameter having different bone densities respectively and human dry mandible segment with copper step wedge were radiographed at 1.0 and 1.2 sec esposure (70 kVp, 7 mA) using one occlusal film and digitized. Eleven rectangular ROIs from 11 cylindric bone phantoms and 4 rectan-gular ROIs from cortical, middle, periodontal regions, and socket of bone were selected. Gaussian blurred Image was subtracted from original image of each ROI and multiplied respectively by 1, 0.8, and 0.5, and then the image was made binary, eroded and dilated once, and skeletonized. The fractal dimension was calculated by means of a box counting method in the software ImageJ. Results : The fractal dimension was decreased gradually with continued bone density decrease showing strong correlations (bone phantom; r> 0.87, bone; r> 0.68) under 70 kVp 1.0 sec M = 0.8. Fractal dimensions showed the significant differerence (p < 0.05) between two different exposure times on the same small ROI of bone phantom. Fractal dimensions between two different sizes of ROI on bone phantom showed the significant differerence (p < 0.05) under 1.2 sec exposure, but did not show it (p > 0.05) under 1.0 sec exposure. Conclusions : Exposure time, ROI size, and modifying factor during subtracting could become impacting on the results of fractal dimension. Fractal analysis with thoroughly evaluated method considering the various impacting factors on the results could be useful in assessing the bone density in dental radiography.