Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Lung tuberculosis detection using x-ray images Subject The topic of the resource Canny edge detection; Graylevel threshold; Median filtering; Tuberculosis; Watershed segmentation; X-Ray Description An account of the resource This research work is based on the various experiments performed for the detection of lung tuberculosis using various methods like filtering, segmentation, feature extraction and classification. The results obtained from these experiments are discussed in this paper. Lung tuberculosis is a bacterial infection that causes more deaths in the world than any other infectious disease. Two billion people are infected with tuberculosis all around the world. Lung tuberculosis is a disease caused by a bacteria known as Mycobacterium tuberculosis or Tubercle bacillus. This research work strives to identify methods by which patients, who require second opinion for an already identified result, can save a lot of money. Once we receive X-ray image an input, pre-processing methods like Gaussian filter, median filter is applied. These filters help to remove unwanted noise and aid to get fine textural features. The output obtained from this is taken as an input and applied to water shed segmentation and gray level segmentation which helps to focus on the lung area of the obtained results. Output from these segmentation methods is fused to get a Region of Interest (ROI). From the ROI, the statistical features like area, major axis, minor axis, eccentricity, mean, kurtosis, skewness and entropy are extracted. Finally, we use KNN, Sequential minimal optimization (SMO), simple linear regression classification methods to detect lung tuberculosis. The results obtained in this paper suggests KNN classifier performs well than the other two classifiers. Research India Publications. Creator An entity primarily responsible for making the resource Antony B.; Nizar Banu P.K. Source A related resource from which the described resource is derived International Journal of Applied Engineering Research, Vol-12, No. 24, pp. 15196-15201. Publisher An entity responsible for making the resource available Research India Publications Date A point or period of time associated with an event in the lifecycle of the resource 2017-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057640992&amp;partnerID=40&amp;md5=409910db5874ad45fde5fea8099644d6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057640992&amp;partnerID=40&amp;md5=409910db5874ad45fde5fea8099644d6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9734562 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Antony B., Department of Computer Science, Christ deemed to be University, Hosur Road, Bhavani Nagar, Bengaluru, 560029, Karnataka, India; Nizar Banu P.K., Department of Computer Science, Christ deemed to be University, Hosur Road, Bhavani Nagar, Bengaluru, 560029, Karnataka, India