A Novel Shape Descriptor with Rotation Angle Estimator

  • 楊 永平

Student thesis: Master's Thesis

Abstract

Object recognition is an important issue in image processing For different object recognition methods we may discuss whether the method includes rotation scaling or translation invariances or not However not every application involves all three invariances In Automated Optical Inspection (ex: Industrial quality testing) for example an application would hope to obtain an estimate on the objects rotation angle and thus has to focus on the rotation variant above the other invariances The application also requires high accuracy and low time complexity to achieve the goal To solve this problem this paper proposes a novel shape descriptor and the associated algorithm The descriptor is contour-based and uses the contour points as an object’s feature The goal is to acquire the similarity between two objects and the difference between their respective rotation angles It can also detect defective areas on the object’s contour The advantage of using contour-based detection as opposed to using a region-based method is that it is able to describe the object’s information more clearly and can reduce outside influences like occlusion brightness and so on With the above advantages the accuracy can also be improved Additionally the proposed will utilize the Polar coordinate system instead of the Cartesian coordinate system The benefit of using said coordinate system is that a pixel’s radius and angle can now be provided as information which is very helpful when capturing the object’s feature
Date of Award2016 Aug 22
Original languageEnglish
SupervisorPei-Yin Chen (Supervisor)

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