Neutrosophy studies the origin, nature, scope of neutralities, and their interactions
with different ideational spectra. It is a new philosophy introduced by Florentin Smarandache that extends fuzzy logic and is
the basis of neutrosophic logic, neutrosophic probability, neutrosophic set theory, and
Because the world is full of indeterminacy, the imperfection of knowledge that a
human receives/observes from the external world also causes imprecision. Neutrosophy
introduces a new concept , which is the representation of indeterminacy.
However, this theory is mostly discussed in physiology and mathematics. Thus,
applications to prove this theory can solve real problems are needed.
Image segmentation is the first and key step in image processing. It is a critical and
essential component of image analysis and pattern recognition. In this dissertation, I
apply neutrosophy to three types of image segmentation: gray level images, breast
ultrasound images, and color images. In gray level image segmentation, neutrosophy
helps reduce noise and extend the watershed method to normal images. In breast
ultrasound image segmentation, neutrosophy integrates two controversial opinions about
speckle: speckle is noise versus speckle includes pattern information. In color image
segmentation, neutrosophy integrates color and spatial information, global and local
information in two different color spaces: RGB and CIE (L*u*v*), respectively. The
experiments show the advantage of using neutrosophy.