Authors :
Divyalakshmi. R, Aswini. P, Bharath. S, Uma Maheswari.
Volume/Issue :
Volume 3 - 2018, Issue 3 - March
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://goo.gl/cFHrFW
Thomson Reuters ResearcherID :
https://goo.gl/3bkzwv
Abstract :
Wireless capsule endoscopy (WCE) has become a widely used diagnostic technique to examine inflammatory bowel diseases and disorders. As one of the most common human worm infections, hookworm is a type of a small tubular structure with grayish white or pinkish translucent body. Automatic hookworm detection is quite a challenging task due to low quality images, presence of additional intestinal matters, complex structure of intestinal tract and varied features in terms of color and texture. Hookworm infection seriously threatens human health, causing intestinal inflammation, progressive iron/protein-deficiency anemia, mucosa damage, and malnutrition of human. This proposed paper demonstratesthe detection of hookworm in human, automatically, by using GLCM, guided filter and later applying morphological processing in order to detect its presence in the intestines.
Keywords :
Hookworm detection, WCE, Texture.
Wireless capsule endoscopy (WCE) has become a widely used diagnostic technique to examine inflammatory bowel diseases and disorders. As one of the most common human worm infections, hookworm is a type of a small tubular structure with grayish white or pinkish translucent body. Automatic hookworm detection is quite a challenging task due to low quality images, presence of additional intestinal matters, complex structure of intestinal tract and varied features in terms of color and texture. Hookworm infection seriously threatens human health, causing intestinal inflammation, progressive iron/protein-deficiency anemia, mucosa damage, and malnutrition of human. This proposed paper demonstratesthe detection of hookworm in human, automatically, by using GLCM, guided filter and later applying morphological processing in order to detect its presence in the intestines.
Keywords :
Hookworm detection, WCE, Texture.
