Real time 3d surface feature extraction on fpga

Date

2010

Author

Tellioğlu, Zafer Haşim

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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.

Subject Keywords

Electrical and Electronics Engineering.

URI

http://etd.lib.metu.edu.tr/upload/12612200/index.pdf
https://hdl.handle.net/11511/19742

Collections

Graduate School of Natural and Applied Sciences, Thesis