• Journal of Information Processing Systems
• /
• v.19 no.1
• /
• pp.33-45
• /
• 2023

This paper proposes an algorithm that automatically converts images into Pipo, painting images using OpenCV-based image processing technology. The existing "purity," "palm," "puzzling," and "painting," or Pipo, painting image production method relies on manual work, so customized production has the disadvantage of coming with a high price and a long production period. To resolve this problem, using the OpenCV library, we developed a technique that automatically converts an image into a Pipo painting image by designing a module that changes an image, like a picture; draws a line based on a sector boundary; and writes sector numbers inside the line. Through this, it is expected that the production cost of customized Pipo painting images will be lowered and that the production period will be shortened.

• Journal of Korea Multimedia Society
• /
• v.25 no.4
• /
• pp.583-599
• /
• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• Journal of Convergence for Information Technology
• /
• v.7 no.4
• /
• pp.229-234
• /
• 2017

The purpose of this study was to investigate 188 university students at Seoul National University and to present self - image data to university students for the development of small and medium human resources. The results of the study are as follows. First, there was a positive correlation between the correlation between the image of the trainee perceived by university students and the self - image, the correlation between the image of the trainee perceived by the university students and the voice image, and the correlation between the voice image and the self - image perceived by university students. Second, as a result of examining whether or not the voice image is mediated in the relationship between the image of the talent and the self - image perceived by university students, Therefore, it is confirmed that as the image level of the talent related to the human resource of SMEs increases, the level of the voice image increases and the self image level also improves accordingly.

• Journal of Korean Ophthalmic Optics Society
• /
• v.17 no.2
• /
• pp.165-170
• /
• 2012

Purpose: The aim of this study was to measure and evaluate changes of visual responses in viewing a 2D and 3D (three-dimensional) image. Methods: The subjects were 44 college students aged 19 to 25 years with normal binocular vision. The visual responses measured were CA/C (convergence accommodation/convergence) ratio, convergence-induced PD(interpupillary distance), accommodative responses, perceived distance in viewing a 3D image. Results: Convergence and accommodative responses in viewing the 3D image were significantly larger (p<0.05) than in 2D. A moderate positive correction was found between CA/C ratio and accommodative response (r = 0.477, p = 0.001). It was indicated that smaller PD had larger depth perception. Convergence in viewing the 3D image was significantly larger (p<0.05) than that at cognitive distance. Conclusions: The visual fatigue may be more intense in larger CA/C ratio and smaller PD when viewing 3D images.

• Journal of the Korea Convergence Society
• /
• v.9 no.2
• /
• pp.119-124
• /
• 2018

The augmented reality(AR) technology enables to acquire various image information at the same time by combining virtual image information with the user's viewpoint. These AR technologies have been used to visualize patients' organs and tissues during surgery and diagnosis in the fields of Image-Guide Operation, Surgical Training, and Image Diagnosis by medical convergence, and provides the most effective surgical methods. In this paper, we study the technical features and application methods of each element technology for medical fusion of AR technology. In the AR technology for medical convergence, display, marker recognition and image synthesis interface technology is essential for efficient medical image. Such AR technology is considered to be a way to drastically improve current medical technology in the fields of image guide surgery, surgical education, and imaging diagnosis.

• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.4
• /
• pp.187-193
• /
• 2012

An image authentication scheme for gray scale image through embedding a digital watermark by quantization of Integer Wavelet Transform (IWT) coefficients of the image is proposed in this paper. Proposed method is designed to detect modification of an image and to identify tampered location of the image. To embed the watermark mid-frequency band of a second level IWT was used. An approximation of the original image based on LL band was stored in LSB bits of the pixel data as a recovery mark for restoration of the image. Watermarked image has achieved a good PSNR of 40 dB compared to original cover image. Restored image quality was also very good with a PSNR of more than 35 dB compared to unmodified watermarked image even when 25% of the received image is cropped. Thus, the proposed method ensures a proper balance between the fidelity of the watermarked image and the quality of the restored image.

• Journal of Information Display
• /
• v.3 no.2
• /
• pp.19-25
• /
• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.8
• /
• pp.74-83
• /
• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• Journal of information and communication convergence engineering
• /
• v.9 no.2
• /
• pp.197-200
• /
• 2011

In this paper, we propose a multi-view stereoscopic image synthesis algorithm for 3DTV system using depth information with an RGB texture from a depth camera. The proposed algorithm synthesizes multi-view images which a virtual convergence camera model could generate. Experimental results showed that the performance of the proposed algorithm is better than those of conventional methods.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.12a
• /
• pp.153-156
• /
• 2000

Recently, there has been studied on feature extraction method for efficient content-based image retrieval. Especially, Many researchers have been studying on extracting feature from color Information, because of its advantages. This paper proposes a feature and its extraction method based on color correlogram that is extracted from color information in an image. the proposed method is computed from the image segmented into two parts; the complex part and the plain part. Our experiments show that the performance of the proposed method is better as compared with that of the original color correlogram method.