• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.7-12
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• 2011

In this paper, we propose the technique detecting interest object region effectively in the images from periscope of submarine based on self-generated template. First, we extract the sea-sky line, and divide it into sky and sea area from background region based on the sea-sky line. In each divided background region, the blocks which can be represented in each background region are set as a reference template. After dividing an image into several same size of blocks, we apply multi template matching to the divided search blocks and histogram template to divide the image into object region and background region. Proposed algorithm is adapted to various images in which objects exist in the background of sea and sky. We verified that proposed algorithm performed properly without given informmed prby prior learning.ropso, regardless of the slope of sea-sky line and the locmed p of object based on sea-sky line, we verified that the objects region was segmented effectively from the input image.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.465-472
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• 2003

For an effective pre-treatment process of a face input image, it is necessary to detect each of face components, calculate the face area, and estimate the rotary angle of the face. A proposed method of this study can estimate an robust result under such renditions as some different levels of illumination, variable fate sizes, fate rotation angels, and background color similar to skin color of the face. The first step of the proposed method detects the estimated face area that can be calculated by both adapted skin color Information of the band-wide HSV color coordinate converted from RGB coordinate, and skin color Information using histogram. Using the results of the former processes, we can detect a lip area within an estimated face area. After estimating a rotary angle slope of the lip area along the X axis, the method determines the face shape based on face information. After detecting eyes in face area by matching a partial template which is made with both eyes, we can estimate Y axis rotary angle by calculating the eye´s locations in three dimensional space in the reference of the face area. As a result of the experiment on various face images, the effectuality of proposed algorithm was verified.