• Fashion & Textile Research Journal
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• v.12 no.1
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• pp.1-9
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• 2010

A purpose of this study was to find out how the casual and formal style clothes of stripe pattern giving variety by pattern direction, pattern width, and contrast coloration have an effect on image of wearers. 432 stimuli were made and 2,800 testee evaluated them using semantic differential scale. As a result, five image dimensions were drawn as a factor of attractiveness, activeness, gracefulness, visibility, and tenderness. In consequence of analysing the image difference by stripe pattern and clothing style, the stripe pattern and clothing style affect image presentation as a significant clue. And besides, as a result of positioning stimuli by image, pattern direction, coloration, and tone combination were important clues that decide image. Consequently, clothing style, stripe pattern, and contrast coloration were made clear as an efficient parameter in image presentation of clothing wearers.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.18-24
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• 2010

In this paper, we address an active ranging system based on laser structured light image for mobile robot application. Since the burdensome correspondence problem is avoidable, the structured light image processing has efficient computation in comparison with the conventional stereo image processing. By using a cylindrical lens in the laser generation, it is possible to convert a point laser into a stripe laser without motorized scan in the proposed system. In order to achieve robustness against environmental illumination noise, we propose an efficient integro-differential image processing algorithm. The proposed system has embedded image processing module and transmits distance data to reduce the computational burden in main control system.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.281-284
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• 2003

In this study, we have proposed the method of moving area detection as the preprocessing step of moving object tracking system. First, we catch the two frames which are different at time in image sequence. We obtain the moving area by using their binary differential image. In differential image, the object area of previous and current frame is present. In the tracking system, the background is changed by camera motion. So, in this case we have to decide which moving area of object is current at time. We obtain the binary edge image of current frame by applying a threshold to the output of an edge detector. Then we performed logical AND operation between the edge image and differential image. As a result of this work moving area of object can be detected.

• Journal of The Korean Association of Information Education
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• v.21 no.5
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• pp.527-535
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• 2017

In this study, we analyzed the image of artificial intelligence recognized by elementary students using semantic differential scale. First, we extracted 23 pairs of image adjectives related to perception of artificial intelligence. Adjectives were classified into three types related to recognition, emotion and ability and 827 elementary students were examined. Image factors were classified into four factors: convenience, technological progress, human-friendliness, and concern. As a result, they showed a clear image that artificial intelligence is clever, new, and complex but exciting. In comparison with variables, female students, coding experience and older students thought that artificial intelligence was more human-friendly and technological progressive.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.473-480
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• 2003

In this paper, we propose a new quadtree coding a1gorithm to improve the performance of the old one. The new algorithm can process any frame of size in standard and reduce encoding and decoding time by decreasing computational load. It also improves the image quality comparing with any old quantizer based on quadtree and zerotree structure. In order for the new algorithm to be applied for real video codec, we analyze the statistical characteristics of coefficients of differential image and add a function that makes It deal with an arbitrary size of image by using new technique while the old one process by block unit. We can also improve the image quality by scaling the coefficient's value from a differential image. By comparing the performance of the new algorithm with quadtree and SPIHT, it Is shown that PSNR is improved, that the computational load is not reduced in encoding and decoding.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.350-353
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• 2013

In this paper, a hardware implementation of phase calculator for extracting 3D depth image from TOF(Time-Of-Flight) sensor is proposed. The designed phase calculator, which adopts redundant binary number systems and a pipelined architecture to improve throughput and speed, performs arctangent operation using vectoring mode of DCORDIC algorithm. Fixed-point MATLAB simulations are carried out to determine the optimized bit-widths and number of iteration. The designed phase calculator is verified by emulating the restoration of virtual 3D data using MATLAB/Simulink and FPGA-in-the-loop verification, and the estimated performance is about 7.5 Gbps at 469 MHz clock frequency.

• Journal of Applied and Pure Mathematics
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• v.5 no.5_6
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• pp.389-406
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• 2023

In the pursuit of enhancing image fusion techniques, this research presents a novel approach for fusing multimodal images, specifically infrared (IR) and visible (VIS) images, utilizing a combination of partial differential equations (PDE) and discrete cosine transformation (DCT). The proposed method seeks to leverage the thermal and structural information provided by IR imaging and the fine-grained details offered by VIS imaging create composite images that are superior in quality and informativeness. Through a meticulous fusion process, which involves PDE-guided fusion, DCT component selection, and weighted combination, the methodology aims to strike a balance that optimally preserves essential features and minimizes artifacts. Rigorous evaluations, both objective and subjective, are conducted to validate the effectiveness of the approach. This research contributes to the ongoing advancement of multimodal image fusion, addressing applications in fields like medical imaging, surveillance, and remote sensing, where the marriage of IR and VIS data is of paramount importance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2317-2337
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• 2015

Cryptography provides an effective solution to secure the communication over public networks. The communication over public networks that includes electronic commerce, business and military services, necessitates the requirement of simple and robust encryption techniques. In this paper, a novel image encryption method which employs calligraphy based hybrid scan and random number is presented. The original image is scrambled by pixel position permutation with calligraphy based diagonal and novel calligraphy based scan patterns. The cipher image is obtained by XORing the scrambled image with random numbers. The suggested method resists statistical, differential, entropy, and noise attacks which have been demonstrated with a set of standard images.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.225-227
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• 1995

An object detection algorithm using a modified IDM(Image Differential Method) is proposed for detecting an object in a level crossing area. The conventional object detection method using LASER light has the deadzone that it cannot detect small objects, while the object detection method using image data in a level crossing area can detect such small objects. But the image data in a level crossing area can be changeable easily because the data is outdoor and sensitive to such surrounding environments as the change of the sun beam, the shadow of cars, and so on. So we resolve these problems by adding the normalization and the process for shadow of the image data in a level crossing area to the basic IDM(Image Differential Method).