• Radiation Oncology Journal
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• v.37 no.1
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• pp.22-29
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• 2019

Purpose: The aim of this study is to evaluate the efficacy and feasibility of four-field box whole brain radiotherapy (FB-WBRT) with tilting baseplate by comparing bilateral WBRT (B-WBRT). Methods and Materials: Between March 2016 and September 2018, 20 patients with brain metastases underwent WBRT using the four-field box technique. WBRT is performed with a dose of 30 Gy in 10 fractions daily. Two computed tomography simulations per person were performed. One was in the traditional supine position for B-WBRT and the other by applying the tilting acrylic supine baseplate to elevate the head by 40° for FB-WBRT. The B-WBRT used the field-in-field technique, which is the most commonly used method in our institution. The FB-WBRT comprised anterior, posterior, and bilateral beams. A wedge was applied in anterior and posterior fields to compensate for skull convexity. Results: The average of Dmean of both parotid glands was 10.2 Gy (range, 3.8 to 17.8 Gy) in B-WBRT and 5.4 Gy (range, 2.0 to 11.7 Gy) in FB-WBRT (p < 0.05). Compared to B-WBRT, FB-WBRT reduced the mean dose of the right and left parotid glands from 10.1 Gy to 4.9 Gy and from 10.4 Gy to 5.8 Gy, respectively (p < 0.05). Further, V₅, V₁₀, V₁₅, V₂₀, and V₂₅ for the parotid gland decreased significantly in FB-WBRT (p < 0.05). The Dmax and Dmean of lens decreased according to the dose-volume histogram. Conclusion: Compared to B-WBRT, FB-WBRT with a tilting baseplate is a simple and effective method that takes feature of noncoplanar beam to protect the parotid gland.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1519-1526
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• 2023

For the first time Aluminium-BariumeZinc oxide nanocomposite (ZABONC) was synthesized by solution combustion method where calcination was carried out at low temperatures (600℃) to study the electromagnetic (EM) (X/γ) radiation shielding properties. Further for characterization purpose standard techniques like PXRD, SEM, UV-VISIBLE, FTIR were used to find phase purity, functional groups, surface morphology, and to do structural analysis and energy band gap determination. The PXRD pattern shows (hkl) planes corresponding to spinel cubic phase of ZnAl₂O4, cubic Ba(NO₃)₂, α and γ phase of Al₂O₃ which clearly confirms the formation of complex nano composite. From SEM histogram mean size of nano particles was calculated and is in the order of 17 nm. Wood and Tauc's relation direct energy band gap calculation gives energy gap of 2.9 eV. In addition, EM (X/γ) shielding properties were measured and compared with the theoretical ones using standard procedures (NaI (Tl) detector and multi channel analyzer MCA). For energy above 356 keV the measured shielding parameters agree well with the theory, while below this value slight deviation is observed, due to the influence of atomic/crystallite size of the ZABONC. Hence synthesized ZABONC can be used as a shielding material in EM (X/γ) radiation shielding.

• Journal of the Semiconductor & Display Technology
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• v.11 no.4
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• pp.49-55
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• 2012

This paper proposes an efficient method of object identification and localization for image recognition. The new proposed algorithm utilizes correlogram back-projection in the YCbCr chromaticity components to handle the problem of sub-region querying. Utilizing similar spatial color information enables users to detect and locate primary location and candidate regions accurately, without the need for additional information about the number of objects. Comparing this proposed algorithm to existing methods, experimental results show that improvement of 21% was observed. These results reveal that color correlogram is markedly more effective than color histogram for this task. Main contribution of this paper is that a different way of treating color spaces and a histogram measure, which involves information on spatial color, are applied in object localization. This approach opens up new opportunities for object detection for the use in the area of interactive image and 2-D based augmented reality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.840-855
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• 2011

In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images. Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding. Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands. A suboptimal feature set is searched by using a threshold selection algorithm. Extensive experiments are performed on four diverse uncompressed image databases. In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.972-974
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• 2009

This paper presents smart regional contrast enhancement technique of partitioned image for local dimming backlight on small-sized mobile display to reach two goals. One is to save the power consumption, and the other to improve contrast ratio of display image. Recently new advanced method is proposed, named local dimming method, that backlight LED is positioned on backside of the display panel. So it is important to partition an image by sub blocks and then post-processing independantly. This means regional contrast enhancement. After partitioning, we compare the mean luminance(Y) value of each sub-block image with the one of original whole image. If some blocks have the mean value lower than the one of whole image, they are processed with the proposed method and others are bypassed. Simultaneously the information of the processed blocks are transferred to BLC(Backlight LED Controller). And then the supply current of each backlight LED is reduced to realize the contrast ratio enhancement and at the same time to power consumption reduction. In addition, we verify this proposed method is free from blocking artifacts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1807-1823
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• 2016

Local Binary Pattern (LBP) and its variants have powerful discriminative capabilities but most of them just consider each LBP code independently. In this paper, we propose sub oriented histograms of LBP for smoke detection and image classification. We first extract LBP codes from an image, compute the gradient of LBP codes, and then calculate sub oriented histograms to capture spatial relations of LBP codes. Since an LBP code is just a label without any numerical meaning, we use Hamming distance to estimate the gradient of LBP codes instead of Euclidean distance. We propose to use two coordinates systems to compute two orientations, which are quantized into discrete bins. For each pair of the two discrete orientations, we generate a sub LBP code map from the original LBP code map, and compute sub oriented histograms for all sub LBP code maps. Finally, all the sub oriented histograms are concatenated together to form a robust feature vector, which is input into SVM for training and classifying. Experiments show that our approach not only has better performance than existing methods in smoke detection, but also has good performance in texture classification.

• Journal of KIISE
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• v.44 no.7
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• pp.692-702
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• 2017

Face detection using the LBP based feature descriptor has issues in that it can not represent spatial information between facial shape and facial components such as eyes, nose and mouth. To address these issues, in previous research, a facial image was divided into a number of square sub-regions. However, since the sub-regions are divided into different numbers and sizes, the division criteria of the sub-region suitable for the database used in the experiment is ambiguous, the dimension of the LBP histogram increases in proportion to the number of sub-regions and as the number of sub-regions increases, the sensitivity to facial orientation rotation increases significantly. In this paper, we present a novel facial region segmentation method that can solve in-plane rotation issues associated with LBP based feature descriptors and the number of dimensions of feature descriptors. As a result, the proposed method showed detection accuracy of 99.0278% from a single facial image rotated in orientation.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.353-362
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• 2006

A data warehouse is a data repository that enables users to store large volume of data and to analyze it effectively. In this research, we investigate an algorithm to establish a multidimensional data cube which is a powerful analysis tool for the contents of data warehouses and databases. There exists an inevitable retrieval overhead in a multidimensional data cube due to the sparsity of the cube. In this paper, we propose a dense sub-cube extraction algorithm that identifies dense regions from a large sparse data cube and constructs the sub-cubes based on the dense regions found. It reduces the retrieval overhead remarkably by retrieving those small dense sub-cubes instead of scanning a large sparse cube. The algorithm utilizes the bitmap and histogram based techniques to extract dense sub-cubes from the data cube, and its effectiveness is demonstrated via an experiment.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.57-65
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• 2009

This paper presents the image contrast enhancement technique suitable for local dimming backlight of small-sized mobile display while achieving the reduction of the power consumption. In addition to the large-sized TFT-LCD, small-sized one has adopted LED for backlight. Since, conventionally, LED was mounted on the side edge of a display panel, global dimming method has been widely used. However, recently, new advanced method of local dimming by placing the LED to the backside of the display panel and it raised the necessity of sub-blocked processing after partitioning the target image. When the sub-blocked image has low brightness, the supply current of a backlight LED is reduced, which gives both enhancement of contrast ratio and power consumption reduction. In this paper, we propose simple and improved image enhancement algorithm suitable for the small-sized mobile display. After partitioning the input image by equal sized blocks and analyzing the pixel information in each block, we realize the primary contrast enhancement by independently processing the sub-blocks using the information such as histogram, mean, and standard deviation values of luminance(Y) component. And then resulting information is transferred to each backlight control unit for local dimming to realize the secondary contrast enhancement as well as reduction of power consumption.