Lung Image Segmentation using Rotation Invariance and Template Matching
Nidhi1, Varun Bhardwaj2
1Nidhi, Department of Computer Engineering,NIT Kurukshetra,
2Varun Bhardwaj Department of Business Intelligence Infosys Technologies
Manuscript received on January 11, 2014. | Revised Manuscript received on January 15, 2014. | Manuscript published on January 25, 2014. | PP:18-23 | Volume-2 Issue-3, January 2014. | Retrieval Number: C0631012314/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The work aims at using the rotation invariant feature and gray scale invariance feature as basis for template matching for identification of nodules of various sizes and texture. The structural textures so obtained are used to describe statistical feature called variance which provide efficient segmentation of lung nodules and helps in clear visualization of nodule boundaries which is important for doctors for analyzing the disease effects. The segmented image so obtained showed all the nodules clearly but the nodules that benign cannot be separated or identified by segmentation. To identify the nodule so obtained the different size templates of nodules were described to identify nodules of particular size and texture. The LBP variance descriptor provided the texture and LBP rotation invariance allowed nodule to be detected irrespective of the orientation of input image.