Show simple item record

dc.contributor.authorKanajal Chandrakanth, Spoorthy
dc.description.abstractEdges in an image characterize object boundaries in an image, which is helpful in image processing and feature extraction in a particular scene. One of the methods used to detect edges in an image is image thresholding, which replaces a pixel in an image with black pixel if an image intensity is less than some constant T. Edge detection is used to classify, interpret and analyze the digital images in various fields such as robots, the sensitive applications in military, etc. A hierarchical multilevel thresholding method for edge detection using the Ant Colony algorithm is used in this paper. Multilevel thresholding technique is applied in this paper based on previous work done by Ashour, A. S., El-Sayed (2014). Further, the results are produced for edge detection of images using ACO algorithm with multilevel thresholding. Both Gray scale images and color images are used to evaluate the efficiency of the algorithm.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.titleImplementation of Multilevel Thresholding Based Ant Colony Optimization Algorithm for Edge Detection of Imagesen_US
dc.typeMaster's paperen_US
dc.date.accessioned2017-08-16T20:25:39Z
dc.date.available2017-08-16T20:25:39Z
dc.date.issued2017
dc.identifier.urihttps://hdl.handle.net/10365/26365
dc.subject.lcshImage processing -- Digital techniques.en_US
dc.subject.lcshImage segmentation.en_US
dc.subject.lcshAnt algorithms.en_US
dc.subject.lcshMathematical optimization.en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentComputer Scienceen_US
ndsu.programSoftware Engineeringen_US
ndsu.advisorLudwig, Simone


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record