Show simple item record

dc.contributor.authorLiew, Eng Keat
dc.date.accessioned2016-05-31T07:00:01Z
dc.date.available2016-05-31T07:00:01Z
dc.date.issued2015-06
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/41779
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractVision is the most advanced of human senses, so it is not surprise that images contribute important role in human perception. Shape recognition is an analogous to computer vision, which is an important field nowadays. Applications of shape recognition found in many areas, such as, manufacturing, medicine, space exploration, defences, etc. This project proposed method of shape recognition to detect circle, triangle, square, and rectangle in an image. The proposed method threshold the three dimensional RGB image input image to a binary image, morphological closing to fill holes of foreground pixel in binary image, and the use of bounding box to calculate object metrics. The object metrics are then compared with predetermined values that characterize the particular shape of an object. The algorithm was first developed in MATLAB and then implemented on raspberry pi. The algorithm applied in raspberry pi is coded in Python and result obtained is shown on a 16 x 2 LCD.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subjectShape recognitionen_US
dc.subjectComputer visionen_US
dc.subjectImage processingen_US
dc.subjectAlgorithmsen_US
dc.titleShape recognition on embedded systemen_US
dc.typeLearning Objecten_US
dc.contributor.advisorDr. Phak Len a/l Eh Kanen_US
dc.publisher.departmentSchool of Computer and Communication Engineeringen_US


Files in this item

Thumbnail
Thumbnail
Thumbnail
Thumbnail
Thumbnail
Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record