• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2881-2894
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• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.131-139
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• 2022

The purpose of this study was to insert a pedicle screw into a pig thoracic vertebrae, a general CT scan(Non MAR), and a thoracic axial image obtained with the Metallic Artifact Reduction for Orthopedic Implants (O-MAR) to reduce artifacts. The image obtained by reconstructing the algorithm (Standard, Soft, Bone, Detail) was used using the image J program. Signal to noise ratio(SNR) and contrast to noise ratio(CNR) were compared and analyzed by obtaining measured values based on the given equation. And this study was to investigate tube voltage and algorithm suitable for CT scan for thoracic pedicle screw insertion. As a result, when non-MAR was used, the soft algorithm showed the highest SNR and CNR at 80, 100, 120, and 140 kVp, On the other hand, when MAR was used, the standard algorithm showed the highest at 80 kVp, and the standard and soft algorithms showed similar values at 100 kVp. At 120 kVp, the Soft and Standard algorithms showed similar values, and at 140 kVp, the Soft algorithm showed the highest SNR and CNR. Therefore, when comparing Non-MAR and MAR, even if MAR was used, SNR and CNR did not increase in all algorithms according to the change in tube voltage. In conclusion, it is judged that it is advantageous to use the Soft algorithm at 80, 100, 120, and 140 kVp in Non MAR, the Standard algorithm at 80 and 100 kVp in MAR, and the Soft algorithm at 120 and 140 kVp. This study is expected to serve as an opportunity to further improve the quality of images by using selective tube voltage and algorithms as basic data to help evaluate images of pedicle screw CT scans in the future.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• ETRI Journal
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• v.24 no.1
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• pp.23-30
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• 2002

MPEG-7 Visual Standard specifies a set of descriptors that can be used to measure similarity in images or video. Among them, the Edge Histogram Descriptor describes edge distribution with a histogram based on local edge distribution in an image. Since the Edge Histogram Descriptor recommended for the MPEG-7 standard represents only local edge distribution in the image, the matching performance for image retrieval may not be satisfactory. This paper proposes the use of global and semi-local edge histograms generated directly from the local histogram bins to increase the matching performance. Then, the global, semi-global, and local histograms of images are combined to measure the image similarity and are compared with the MPEG-7 descriptor of the local-only histogram. Since we exploit the absolute location of the edge in the image as well as its global composition, the proposed matching method can retrieve semantically similar images. Experiments on MPEG-7 test images show that the proposed method yields better retrieval performance by an amount of 0.04 in ANMRR, which shows a significant difference in visual inspection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1390-1393
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• 2004

In the present industry, three-dimensional colored shape has required for realistic prototype in rapid manufacturing. Z-corporation developed 3D printer which can color three-dimensional prototype but this process can't be adopted to other rapid prototype products and spend much time and cost coloring 3D shape. In this study a new coloring process on three-dimensional surface is proposed for realistic prototype. Three-dimensional surface coloring apparatus is composed of HP ink jet head and X-Y plotter. Distance and angle between ink jet nozzle and 3D surface are set as process parameter. Based on the experiment of process parameters, it is shown that distance and angle affected on printed image on 3D surface. Circle and line shape are chosen as standard image shape because the shape has widely used as standard in 2D printing. Consequently, the distorted image on 3D surface is corrected by transformed input image data.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.487-490
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• 2011

This paper presents splitting and merging algorithm based on adaptive thresholding. The algorithm first divides the image into blocks, and then compares each block using the calculated thresholding value. The blocks which are same are merged using the certain threshold value and different blocks are split unless it satisfies the threshold value. When the block has been merged, maximum and minimum block sizes are determined then the average block size is determined. After the average block size is determined the average intensity and standard deviation of average block is calculated. The process of thresholding is applied to binarize the image. Finally, the experimental results show that the proposed method distinguishes clearly the background with text in the document image.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.27-31
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• 1994

Intravascular ultrasound images of coranary artery contain very important informations on heart disease. The intimal contours on the image show informations and data to examine intravascular problems of patients. A new computation algorithm to detect the intimal and adventitial contours from the intravascular images was developed. An Image processing on gray level image was used. It uses arrays of pixels in each radial lines on the images. A "Robert" filter was adopted at first step for one dimensional image processing. Some other calculation techniques were developed to inclose the accuracy of automatically detected contours. The standard contour data to compare with automatically detected contour data were obtained through manually tracing by experienced cardiological medical doctors. The result of the new algorithm shows high accuracy of 80 % matching with the standard contour data.

• Transactions of the Society of Information Storage Systems
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• v.5 no.2
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• pp.89-95
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• 2009

We setup the system to measure the noise characteristics of the 5M complementary metal-oxide semiconductor (CMOS) image sensor by generic measurement indicator of Standard mobile imaging architecture (SMIA) which is one of internal standard of mobile imaging architecture. To evaluate the effect of environment and setting parameters, such as temperature and integration time, we measure the variation of the dark signal, dynamic range and fixed pattern noise of image sensor. We also detect the number of defective pixels and cluster defects defined as adjacent single defect pixels at 5M CMOS image sensor. Then, we find the existence of some cluster defects in experiment, which are not expected in calculation.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.88-88
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• 2002

Satellite Image archiving system requires large storage and long transmission time. A simple and cheap way of overcoming these limitations is to increase the compression ratio. However this requires a feasibility study for accurate applications. Here, a new still image compression standard is being developed, the JPEG2000. It provides lossless and lossy compression, progressive transmission by pixel accuracy and by resolution, region-of-interest coding, user-defined tiling size, random codestream access and processing etc. In this study, we will briefly introduce the JPEG2000 compression standard which provides a new compression technique based on the wavelet technology and offers better compression ratios, and evaluate the compression ratios of JPEG2000 for satellite image by performing various image quality tests. Also, we will compare brief test result using the commercial remote sensing software.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.36-42
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• 1997

This paper presents a new design technique for performing high quality low bit rate image compression. A hybrid coder(HC) which combines Mean Removed Important Coefficient Selection based JPEG(MR-ICS-JPEG) and Adaptive Vector Quantization (AVQ) is proposed. A new quantization table is developed using the Important Coefficient Selection(ICS) method; the importance of each coefficient is determined using the orthonormal property of the DCT. This quantization table is applied to standard JPEG with mean removal(MR) strategy before processing. This scheme, called MR-ICS-JPEG, produces more than 2 dB enhanced performance in terms of PSNR over standard JPEG. A set of homogeneous codebooks is generated by homogeneous training vectors. Before compression, an image is uniformly divided into 8${\times}$8 blocks. Low detail regions such as backgrounds are roughly coded by AVQ while high detail regions such as edges or curves are finely coded by the proposed MR-ICS-JPEG. This hybrid coder procuces consistently about 3 dB improved performance in terms of PSNR over standard JPEG.