• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• 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.

• Progress in Medical Physics
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• v.25 no.1
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• pp.37-45
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• 2014

The accuracy and uniformity of CT numbers are the main causes of radiation dose calculation error. Especially, for the dose calculation based on kV-Cone Beam Computed Tomography (CBCT) image, the scatter affecting the CT number is known to be quite different by the object sizes, densities, exposure conditions, and so on. In this study, the scatter impact on the CBCT based dose calculation was evaluated to provide the optimal condition minimizing the error. The CBCT images was acquired under three scatter conditions ("Under-scatter", "Over-scatter", and "Full-scatter") by adjusting amount of scatter materials around a electron density phantom (CIRS062, Tissue Simulation Technology, Norfolk, VA, USA). The CT number uniformities of CBCT images for water-equivalent materials of the phantom were assessed, and the location dependency, either "inner" or "outer" parts of the phantom, was also evaluated. The electron density correction curves were derived from CBCT images of the electron density phantom in each scatter condition. The electron density correction curves were applied to calculate the CBCT based doses, which were compared with the dose based on Fan Beam Computed Tomography (FBCT). Also, 5 prostate IMRT cases were enrolled to assess the accuracy of dose based on CBCT images using gamma index analysis and relative dose differences. As the CT number histogram of phantom CBCT images for water equivalent materials was fitted with a gaussian function, the FHWM (146 HU) for "Full-scatter" condition was the smallest among the FHWM for the three conditions (685 HU for "under scatter" and 264 HU for "over scatter"). Also, the variance of CT numbers was the smallest for the same ingredients located in the center and periphery of the phantom in the "Full-scatter" condition. The dose distributions calculated with FBCT and CBCT images compared in a gamma index evaluation of 1%/3 mm criteria and in the dose difference. With the electron density correction acquired in the same scatter condition, the CBCT based dose calculations tended to be the most accurate. In 5 prostate cases in which the mean equivalent diameter was 27.2 cm, the averaged gamma pass rate was 98% and the dose difference confirmed to be less than 2% (average 0.2%, ranged from -1.3% to 1.6%) with the electron density correction of the "Full-scatter" condition. The accuracy of CBCT based dose calculation could be confirmed that closely related to the CT number uniformity and to the similarity of the scatter conditions for the electron density correction curve and CBCT image. In pelvic cases, the most accurate dose calculation was achievable in the application of the electron density curves of the "Full-scatter" condition.