• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.210-218
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• 2002

This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of $512{\times}512-pixel$, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.

• Sleep Medicine and Psychophysiology
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• v.24 no.1
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• pp.46-54
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• 2017

Objectives: Domestic violence is related to many psychiatric diseases, such as depression, anxiety disorder, and PTSD. Heart rate variability (HRV) is an index of autonomic control of the heart and is related to cardiovascular and emotional disorders. Although there have been some studies on the effects of domestic violence on women's mental health, relatively little information is available on HRV in this population. The aim of this study is to investigate demographic data, psychological features, and HRV in female victims of domestic violence and difference between Korean and foreign female victims. Methods: A total of 210 female victims of domestic violence (166 Korean women and 44 foreign women) were recruited for this study. Psychological symptoms were measured using the Hamilton Rating Scale for Anxiety (HAM-A), Hamilton Rating Scale for Depression (HAM-D), and Impact of Event Scale-Revised (IES-R). HRV measures were assessed by time-domain and frequency-domain analyses. Results: The mean score of HAM-A was 13.81, that of HAM-D was 12.92, and that of IES-R was 33.61 ; there were no significant differences between Korean and foreign women in these measures. In HRV time domain analyses, approximate entropy (ApEn) was significantly increased in foreign women compared to the Korean women. The square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) was significantly decreased in foreign women compared to Korean women. There were no significant differences in the other HRV variables between Korean and foreign women. Conclusion: Female victims of domestic violence in Korea are associated with depression, anxiety, and PTSD symptoms. The physiologic factors of a female victim's nationality could be related to higher ApEn and lower RMSSD in foreign female victims. These findings have important implications for future study to study the relationships among ethnic and environmental factors and HRV variables.