Feature point detection algorithms have been widely used in the fields of object recognition, panorama stitching, and robot navigation. SIFT algorithm is a robust feature detection method widely used in image processing and computer vision. This design proposes a SIFT algorithm based on FPGA development platform implementation, which reduces the computational complexity and improves the processing speed by adopting a pipelined architecture. The matching results show that the algorithm has good invariance to image rotation, illumination, affine, scale and can meet the needs of feature matching, and there is a certain practical application value.
To overcome the limitations of software demodulation in laser vibration measurement, a hardware demodulation scheme based on a field-programmable gate array (FPGA) is designed. The reference signal is synthesized using direct digital frequency synthesis and mixed with the Doppler signal. An orthogonal baseband signal is then generated through Butterworth low-pass filtering. Subsequently, a nonlinear error compensation algorithm is introduced to rectify errors. The CORDIC algorithm is applied for inverse tangent demodulation of the laser signal, while a phase detuning algorithm addresses signal hopping issues. Following data processing, the fast Fourier algorithm is used for time-frequency analysis of the vibration data signal. The proposed algorithm undergoes theoretical analysis and experimental verification, ensuring real-time vibration detection and meeting high precision requirements. This offers a more concise and efficient solution for laser vibration measurement systems.
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