• Textile Coloration and Finishing
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• v.18 no.5 s.90
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• pp.61-71
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• 2006

This paper addresses the factors hindering the image quality of lines in inkjet printed on polyester fabric as printing media. Lines were printed onto different types of polyester fabrics in warp and filling directions. Line image quality including line width, edge blurriness, and edge raggedness was assessed. The effect of capillary wicking on line image quality of printed spun polyester fabric is discussed. The factors on the image quality include printing position(top of the yam or between the yarn), printing direction(warp or filling), yarn structures(filament or spun), thread size(yam or fiber), finishing, and ink properties(evaporation rate). More than 30% differences in image quality results were observed by changing the printing location on the spun polyester fabric. The best results of the image quality were obtained with the printed plain and spun polyester fabrics. The fiber sizes may affect capillary size; therefore, the image quality can be dissimilar. Types of finishing materials and inks greatly improve the line image quality on spun polyester fabrics.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.132-139
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• 2024

In this paper, we proposed an effective technique that uses location-based encryption technique and spatial encryption technique to improve security vulnerabilities in previous reversible data hiding technique that can hide twice as much confidential data as the NSAS technique. If the proposed technique is applied to hide confidential data in an image, the same amount of confidential data can be hidden compared to the previous technique, but the security of confidential data is greatly enhanced. By hiding confidential data in an image using the proposed technique, high-quality stego-image can be generated, making it impossible to visually distinguish whether confidential data is hidden in the image. Additionally, confidential data can be restored from stego-image without loss, and the original cover image can also be restored without loss. Through experiments, it was confirmed that when confidential data is hidden by applying the proposed technique, the quality of the stego-image is maintained up to 39.73dB, and the security of the stego-image is greatly strengthened.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.

• Journal of KIISE
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• v.43 no.4
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• pp.437-449
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• 2016

Previous image processing techniques based on plane-to-plane transformations cannot be utilized for spherical panoramic images. In this paper, we propose a new method to inpaint a spherical panoramic image using exemplar, which is deformed by the location of the patch. Our proposed method makes the deformed exemplar patch by latitude and uses it as the reference patch to restore the damaged area. The exemplar-based inpainting method is based on the planar image coordinate system and thus the classical method cannot be applied to the spherical panoramic image. The merit of our proposed method is the fact that it is not dependent on the location of the damaged area. From the experimental results, we proved that our proposed method satisfies the original purpose of the exemplar-based inpainting technique for the spherical panoramic image.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.882-897
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• 2020

Recently, the use of immersive media contents representing Panorama and 360° video is increasing. Since the viewing angle is limited to generate the content through a general camera, image stitching is mainly used to combine images taken with multiple cameras into one image having a wide field of view. However, if the parallax between the cameras is large, parallax distortion may occur in the stitched image, which disturbs the user's content immersion, thus an image stitching overcoming parallax distortion is required. The existing Seam Optimization based image stitching method to overcome parallax distortion uses energy function or object segment information to reflect the location information of objects, but the initial seam generation location, background information, performance of the object detector, and placement of objects may limit application. Therefore, in this paper, we propose an image stitching method that can overcome the limitations of the existing method by adding a weight value set differently according to the type of object to the energy value using object detection based on deep learning.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.997-1007
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• 2015

In this paper, we propose a method for automatically analyzing the bone formation in a mouse model of frontal bone defect. We perforate two holes of 0.8mm diameter in the frontal bone and observe the bone formation process using a micro CT. Because the conventional analysis software of the micro CT does not support automatic analysis of the bone formation status, we have to use a manual analysis method. However the manual analysis is very cumbersome and requires a lot of time, we propose an automatic analysis method. It rotates the image around three axes directions so that the mouse's skull come into regular position. It calculates the cumulative image of the voxel values for the perforated bone surface. It estimates the hole location by finding the darkest point in the cumulative image. The proposed method was applied to 24 CT images of saline administration group and PTH administration group and hole location was estimated. BV/TV index was calculated for the estimated hole to evaluate the bone formation status. Experimental results showed that bone formation process is more active in PTH administration group. The method proposed in this paper could replace successfully the cumbersome and time consuming manual job.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.474-485
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• 2001

This paper proposes a user-key-based fragile watermarking for detecting image modification. The embedding data in a form of binary image for authentication are inserted to the DCT coefficients of each block of the given image. To minimize possible exposure of being watermarked and the location of insertion, it is proposed to utilize a user-specific key in randomizing those information. Each DCT block hides one bit of data, all of which represent the user-specific authentication data. Experiments with 5 real images demonstrate that the proposed method not only detects whether there is modification or not, but also the actual location of modification with minimal visual deterioration. However, the proposed method has room for improvement against its loss of watermark by an attack of compression by more than 50%.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.385-399
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• 2017

Nowadays, with the development of signal processing technique, the protection to the integrity and authenticity of images has become a topic of great concern. A blind image authentication technology with high tamper detection accuracy for different common attacks is urgently needed. In this paper, an improved fragile watermarking method based on local binary pattern (LBP) is presented for blind tamper location in images. In this method, a binary watermark is generated by LBP operator which is often utilized in face identification and texture analysis. In order to guarantee the safety of the proposed algorithm, Arnold transform and logistic map are used to scramble the authentication watermark. Then, the least significant bits (LSBs) of original pixels are substituted by the encrypted watermark. Since the authentication data is constructed from the image itself, no original image is needed in tamper detection. The LBP map of watermarked image is compared to the extracted authentication data to determine whether it is tampered or not. In comparison with other state-of-the-art schemes, various experiments prove that the proposed algorithm achieves better performance in forgery detection and location for baleful attacks.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.287-294
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• 2010

TOF technique is one of the skills that can obtain the object's 3D depth information. But depth image has low resolution and fingertip occupy very small region, so, it is difficult to find the precise fingertip's 3D information by only using depth image from TOF camera. In this paper, we estimate fingertip's 3D location using Arm Model and reliable hand's 3D location information that is modified by hexahedron as hand model. Using proposed method we can obtain more precise fingertip's 3D information than using only depth image.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.212-226
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• 2014

This paper presents the design and implementation of a pipelined architecture and a method for real-time human detection using depth image from a Time-of-Flight (ToF) camera. In the proposed method, we use Euclidean Distance Transform (EDT) in order to extract human body location, and we then use the 1D, 2D scanning window in order to extract human joint location. The EDT-based human extraction method is robust against noise. In addition, the 1D, 2D scanning window helps extracting human joint locations easily from a distance image. The proposed method is designed using Verilog HDL (Hardware Description Language) as the dedicated hardware architecture based on pipeline architecture. We implement the dedicated hardware architecture on a Xilinx Virtex6 LX750 Field Programmable Gate Arrays (FPGA). The FPGA implementation can run 80 MHz of maximum operating frequency and show over 60fps of processing performance in the QVGA ($320{\times}240$) resolution depth image.