• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.4
• /
• pp.479-488
• /
• 2002

In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.

• Journal of the Korean Chemical Society
• /
• v.55 no.3
• /
• pp.385-391
• /
• 2011

The time-dependent density functional theory (TDDFT) method has been carried out to investigate the excitedstate hydrogen-bonding dynamics of phenol-$(H_2O)_2$ complex. The geometric structures and infrared (IR) spectra in ground state and different electronically excited states ($S_1$ and $T_1$) of the hydrogen-bonded complex have been calculated using the density functional theory (DFT) and TDDFT method. A ring of three hydrogen bonds is formed between phenol and two water molecules. We have demonstrated that the intermolecular hydrogen bond $O_1-H_2{\cdots}O_3-H$ of the three hydrogen bonds is strengthened in $S_1$ and $T_1$ states. In contrast, the hydrogen bond $O_5-H_6{\cdots}O_1-H$ is weakened in $S_1$ and $T_1$ states. These results are obtained by theoretically monitoring the changes of the bond lengths of the hydrogen bonds and hydrogen-bonding groups in different electronic states. The hydrogen bond $O_1-H_2{\cdots}O_3-H$ strengthening in both the $S_1$ and $T_1$ states is confirmed by the calculated stretching vibrational mode of O-H (phenol) being red-shifted upon photoexcitation. The hydrogen bond strengthening and weakening behavior in electronically excited states may exist in other ring structures of phenol-$(H_2O)_n$.

• Journal of the Korean Society of Radiology
• /
• v.10 no.1
• /
• pp.45-51
• /
• 2016

The purpose of this study was tried to remove the noise and improve the spatial resolution in the computed tomography (CT) by using anisotropic 2-dimensional (2D) diffusion based filter. We used 4-channel multi-detector CT and american association of physicists in medicine (AAPM) phantom was used for CT performance evaluation to evaluate the image quality. X-ray irradiation conditions for image acquisition was fixed at 120 kVp, 100 mAs and scanned 10 mm axis with ultra-high resolution. The improvement of anisotropic 2D diffusion filtering that we suggested firstly, increase the contrast of the image by using histogram stretching to the original image for 0.4%, and multiplying the individual pixels by 1.2 weight value, and applying the anisotropic diffusion filtering. As a result, we could distinguished five holes until 0.75 mm in the original image but, five holes until 0.40 mm in the image with improved anisotropic diffusion filter. The noise of the original image was 46.0, the noise of the image with improved anisotropic 2D diffusion filter was decreased to 33.5(27.2%). In conclusion improved anisotropic 2D diffusion filter that we proposed could remove the noise of the CT image and improve the spatial resolution.