• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.601-607
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• 2018

Median filtering is a nonlinear method which is known to be effective in removing impulse noise while preserving local image structure relatively well. However, it could still suffer the smearing phenomena of edges and fine details into neighbors due to undesirable influence from the pixels whose values are far off from the true value of the pixel at hand. This drawback mainly comes from the fact that median filters typically employ a regular shape window for collecting the pixels used in the filtering operation. In this paper, we propose a median filtering method which employs an irregular shape filter window in collecting neighboring pixels around the pixel to be denoised. By employing an irregular shape window, we can achieve good noise suppression while preserving image details. Experimental results have shown that our approach is superior to regular window-based methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.426-429
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• 2004

To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.

• Journal of Biosystems Engineering
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• v.33 no.3
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• pp.196-203
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• 2008

Hybrid robust image processing algorithm to extract visual features of melon during the cultivation was developed based on a wireless tele-operative interface. Features of a melon such as size and shape including position were crucial to successful task automation and future development of cultivation data base. An algorithm was developed based on the concept of hybrid decision-making which shares a task between the computer and the operator utilizing man-computer interactive interface. A hybrid decision-making system was composed of three modules such as wireless image transmission, task specification and identification, and man-computer interface modules. Computing burden and the instability of the image processing results caused by the variation of illumination and the complexity of the environment caused by the irregular stem and shapes of leaves and shades were overcome using the proposed algorithm. With utilizing operator's teaching via LCD touch screen of the display monitor, the complexity and instability of the melon identification process has been avoided. Hough transform was modified for the image obtained from the locally specified window to extract the geometric shape and position of the melon. It took less than 200 milliseconds processing time.