Research Article
Combination of Adaptive Thresh old Algorithm, Watershed and Top-Hat Transform on Image Segmentation Uneven Lighting
@INPROCEEDINGS{10.4108/eai.20-1-2018.2281934, author={Maranto Tua Halomoan and Muhammad Zarlis and Herman Mawengkang}, title={Combination of Adaptive Thresh old Algorithm, Watershed and Top-Hat Transform on Image Segmentation Uneven Lighting}, proceedings={Proceedings of the 1st Workshop on Multidisciplinary and Its Applications Part 1, WMA-01 2018, 19-20 January 2018, Aceh, Indonesia}, publisher={EAI}, proceedings_a={WMA-1}, year={2019}, month={9}, keywords={image segmentation adaptive threshold watershed top-hat transform}, doi={10.4108/eai.20-1-2018.2281934} }- Maranto Tua Halomoan
Muhammad Zarlis
Herman Mawengkang
Year: 2019
Combination of Adaptive Thresh old Algorithm, Watershed and Top-Hat Transform on Image Segmentation Uneven Lighting
WMA-1
EAI
DOI: 10.4108/eai.20-1-2018.2281934
Abstract
In the previous Saini and Dutta research, there is still a lack of perfect segmentation in the form of window shadows and by examining Cheng and Jun's research, where segmentation on illuminated imagery that has uneven illumination can produce perfect segmentation. In this research, a combination of Adaptive Threshold, Watershed and Top-Hat Transform algorithms is used to segment the image that has uneven lighting. The result of the image segmentation test which has uneven illumination with Adaptive Threshold, Watershed, Top-Hat and Combination algorithm obtained that the smallest value of MSE is in Segmentation result of Combination algorithm and the largest one is in Adaptive Threshold algorithm while the smallest PSNR value is in combination algorithm and the largest is on the Adaptive Threshold algorithm.
