Towards Feature Detection based on Morphology of Objects on Image

FieldValue
dc.contributor.authorSolis Montero, Andres
dc.date.accessioned2013-11-07T19:30:22Z
dc.date.available2013-11-07T19:30:22Z
dc.date.created2010
dc.date.issued2010
dc.identifier.citationSource: Masters Abstracts International, Volume: 49-02, page: 1233.
dc.identifier.urihttp://hdl.handle.net/10393/28558
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-19332
dc.description.abstractThis thesis describes a new line segment detection and extraction algorithm for computer vision, image segmentation, and shape recognition applications. This algorithm uses a compilation of different image processing techniques such as normalization, Gaussian smooth, automatic threshold, and Laplace edge detection to extract edge contours from color input images. Contours of each connected component are divided into short segments, which are classified by their orientation into about ten discrete categories. Straight lines are recognized as the minimal number of such consecutive short segments with the same direction. This solution indeed gives us more precise line segments (including line endpoints) and requires a shorter time than the widely used Hough Transform algorithm for detecting line segments given any orientation and location inside an image. Its easy implementation, simplicity, parameter minimization, speed, ability to split an edge into straight line segments using the actual morphology of objects, accuracy and the use of OpenCV library are key features and advantages of the proposed approach. The algorithm was tested on several simple shape images as well as on real pictures, yielding a more accurate resemblance of straight lines in accordance with the human perception of line taxonomy. The line detection algorithm introduced here requires few parameters and is robust to standard image transformations such as rotation, scaling and translation. Furthermore, some of these parameters are selected by automatic unsupervised methods, thus improving the expected algorithm outcome in terms of the stated problem. Several experimental results are presented to support the validity of the algorithm.
dc.format.extent88 p.
dc.language.isoen
dc.publisherUniversity of Ottawa (Canada)
dc.subject.classificationComputer Science.
dc.titleTowards Feature Detection based on Morphology of Objects on Image
dc.typeThesis
dc.degree.nameM.C.S.
dc.degree.levelMasters
CollectionTh├Ęses, 1910 - 2010 // Theses, 1910 - 2010

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