• Progress in Medical Physics
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• v.15 no.2
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• pp.70-76
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• 2004

The most important work for early detection of liver cancer and decision of its characteristic and location is good segmentation of a liver region from other abdominal organs. This paper proposes a fully automatic liver segmentation algorithm based on the abdominal morphology characteristic as an easy and efficient method. Multi-modal threshold as pre-processing is peformed and a spine is segmented for finding morphological coordinates of an abdomen. Then the liver region is extracted using C-class maximum a posteriori (MAP) decision and morphological filtering. In order to estimate results of the automatic segmented liver region, area error rate (AER) and correlation coefficients of rotational binary region projection matching (RBRPM) are utilized. Experimental results showed automatic liver segmentation obtained by the proposed algorithm provided strong similarity to manual liver segmentation.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.317-326
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• 2004

This paper presents a new method for the detection of multiple pedestrians and tracking of a specific pedestrian using color information from a moving camera. We first extract motion vector on the input image using BMA. Next, a difference image is calculated on the basis of the motion vector. The difference image is converted to a binary image. The binary image has an unnecessary noise. So, it is removed by means of the proposed noise deletion method. Then, we detect pedestrians through the projection algorithm. But, if pedestrians are very adjacent to each other, we separate them using RGB color information. And we track a specific pedestrian using RGB color information in center region of it. The experimental results on our test sequences demonstrated the high efficiency of our approach as it had shown detection success ratio of 97％ and detection failure ratio of 3％ and excellent tracking.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4B
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• pp.353-364
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• 2002

In this paper, a new onto-digital stereo object-tracking system using hierarchical digital algorithms and optical BPEJTC is proposed. This proposed system can adaptively track a moving target by controlling the convergence of stereo camera. firstly, the target is detected through the background matching of the sequential input images by using optical BPEJTC and then the target area is segmented by using the target projection mask which is composed by hierarchical digital processing of image subtraction, logical operation and morphological filtering. Secondly, the location's coordinate of the moving target object for each of the sequential input frames can be extracted through carrying out optical BPEJTC between the reference image of the target region mask and the stereo input image. Finally, the convergence and pan/tilt of stereo camera can be sequentially controlled by using these target coordinate values and the target can be kept in tracking. Also, a possibility of real-time implementation of the adaptive stereo object tracking system is suggested through optically implementing the proposed target extraction and convergence control algorithms.