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  5. Effect of image enhancement on watershed segmentation

Effect of image enhancement on watershed segmentation

 Al-Janabi Aqeel Bahp Tarkhan, L. Shuvalova
Системи обробки інформації. — 2014. — № 8(124). С. 3-7.
UDK 4.932
Article language: english
Annotations languages:

Annotation: In this paper we have showed different types of noise and filters to remove noise from Image and analyze that what exact difference it makes when it comes to segmentation of the Image(via watershed Algorithm ). The image processing part consists of image acquisition of noisy image. This part consists of several image-processing techniques. First, we adding the noise in the image, then applying two types of filters to remove noise from the image. Here we use Mean Filter and median (3*3) to remove the noise. Then applying watershed Algorithm on Ideal image to be the ideal result, and applying watershed algorithm on both filtered images. Finally comparing these results with ideal result by using of Chi square (χ2) test, to get the best of these filters to be the selected filter for using with watershed algorithm.

Keywords: Image enhancement, noise type, mean filter, median filter, Image segmentation, watershed algorithm
Information about the authors of publication:
Al-Janabi Aqeel Bahp Tarkhan, Shuvalova, L.A. (2014), Effect of image enhancement on watershed segmentation, Information Processing Systems, Vol. 8(124), pp. 3-7.