A New Image Segmentation Algorithm and Its Application in Lettuce Object Segmentation
Abstract: Lettuce image
segmentation which based on computer image processing is the premise of
non-destructive testing of lettuce quality. The traditional 2-D maximum entropy
algorithm has some faults, such as low accuracy of segmentation, slow speed,
and poor anti-noise ability. As a result, it leads to the problems of poor
image segmentation and low efficiency. An improved 2-D maximum entropy
algorithm is presented in this paper. It redistricts segmented regions and
furtherly classifies the segmented image pixels with the method of the minimum
fuzzy entropy, and reduces the impact of noise points, as a result the image
segmentation accuracy is improved. The improved algorithm is used to lettuce
object segmentation, and the experimental results show that the improved
segmentation algorithm has many advantages compared with the traditional 2-D
maximum entropy algorithm, such as less false interference, strong anti-noise
ability, good robustness and validity.
Author: Jun Sun, Yan Wang, Xiaohong
Wu, Xiaodong Zhang, Hongyan Gao
Journal Code: jptkomputergg120083
