TITLE:
Foreign Fiber Image Segmentation Based on Maximum Entropy and Genetic Algorithm
AUTHORS:
Liping Chen, Xiangyang Chen, Sile Wang, Wenzhu Yang, Sukui Lu
KEYWORDS:
Foreign Fibers, Image Segmentation, Maximum Entropy, Genetic Algorithm
JOURNAL NAME:
Journal of Computer and Communications,
Vol.3 No.11,
November
19,
2015
ABSTRACT: In machine-vision-based systems
for detecting foreign fibers, due to the background of the cotton layer has the
absolute advantage in the whole image, while the foreign fiber only account for
a very small part, and what’s more, the brightness and contrast of the image
are all poor. Using the traditional image segmentation method, the segmentation
results are very poor. By adopting the maximum entropy and genetic algorithm,
the maximum entropy function was used as the fitness function of genetic
algorithm. Through continuous optimization, the optimal segmentation threshold
is determined. Experimental results prove that the image segmentation of this
paper not only fast and accurate, but also has strong adaptability.