Optimización de filtros de visión artificial mediante C/ASM en arquitecturas x86-64

Optimización de filtros de visión artificial mediante C/ASM en arquitecturas x86-64 Mejorar el rendimiento de filtros de visión artificial implementándolos en C y ASM ABSTRACT The present project proposes a proof of concept for the conversion of RGB images to grayscale. It focuses on the design of C/ASM software for the transformation of RGB images into grayscale. A hybrid architecture is proposed, employing C for file and memory management, and Assembly Language (x86 64) for arithmetic processing. The research centers on optimizing memory access and leveraging CPU registers to reduce execution time when processing high resolution static images, establishing a technical foundation for more complex computer vision algorithms such as Sobel or Canny filters, among others. Keywords RGB-to-Grayscale Conversion; Image Processing; Computer Vision; SIMD Optimization; x86-64 Architecture.