Open AccessAn Imaging Based Lung Tissue and Spread Level Detection for Early Detection of Cancer
Author(s) -
B. Thiyaneswaran,
K. Anguraj,
R. Kandiban,
N. S. Yoganthan,
J. Jayanthi
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3168.078219
Subject(s) - thresholding , pixel , artificial intelligence , computer vision , computer science , grayscale , canny edge detector , rgb color model , median filter , otsu's method , morphological gradient , edge detection , gaussian filter , pattern recognition (psychology) , image processing , image (mathematics)
A tissues in the human organs is mainly due to the disease. The spread of tissue indicates the increase in disease level. The tissues and level of tissue in the organ may require for physician assessment. The proposed work is used to detect the tissue level in lungs. An early detection of tissue may leads to detect the cancer cell. The RGB color input image is converted into gray scale image. The gaussian noise is applied on the gray image. The median filter is applied to project the tissue pixels. The canny edge detection is applied on the filtered image to detect the boundary regions. The gradient magnitude operation is performed to project the edges of tissue. A watershed transform is applied on the gradient image to perform the morphological operation. A morphological area open and area close operation is performed along with reconstruction which highlights the tissue area from the lungs. Super imposing morphology with the regional maximum pixel operation is performed to differentiate tissue pixels. The tissue area is retained and all other area pixels are replaced by logic ‘0’ pixels using Otsu’s global thresholding method. The tissue portion is cropped using the OAD regions.