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Real Time 3d Surface Feature Extraction On Fpga

Three dimensional (3D) surface feature extractions based on mean (H) and
Gaussian (K) curvature analysis of range maps, also known as depth maps, is an
important tool for machine vision applications such as object detection,
registration and recognition. Mean and Gaussian curvature calculation algorithms
have already been implemented and examined as software. In this thesis,
hardware based digital curvature processors are designed. Two types of real time
surface feature extraction and classification hardware are developed which
perform mean and Gaussian curvature analysis at different scale levels. The
techniques use different gradient approximations. A fast square root algorithm
using both LUT (look up table) and linear fitting technique is developed to
calculate H and K values of the surface described by the 3D Range Map formed
by fixed point numbers. The proposed methods are simulated in MatLab software
and implemented on different FPGAs using VHDL hardware language.
Calculation times, outputs and power analysis of these techniques are compared to
CPU based 64 bit float data type calculations.

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12612200/index.pdf
Date01 July 2010
CreatorsTellioglu, Zafer Hasim
ContributorsUlusoy, Ilkay
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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