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Journal of Real-Time Image Processing

, Volume 14, Issue 3, pp 647–665 | Cite as

Robust feature extraction algorithm suitable for real-time embedded applications

  • Abiel Aguilar-González
  • Miguel Arias-Estrada
  • François Berry
Special Issue Paper

Abstract

Smart cameras integrate processing close to the image sensor, so they can deliver high-level information to a host computer or high-level decision process. One of the most common processing is the visual features extraction since many vision-based use-cases are based on such algorithm. Unfortunately, in most of cases, features detection algorithms are not robust or do not reach real-time processing. Based on these limitations, a feature detection algorithm that is robust enough to deliver robust features under any type of indoor/outdoor scenarios is proposed. This was achieved by applying a non-textured corner filter combined to a subpixel refinement. Furthermore, an FPGA architecture is proposed. This architecture allows compact system design, real-time processing for Full HD images (it can process up to 44 frames/91.238.400 pixels per second for Full HD images), and high efficiency for smart camera implementations (similar hardware resources than previous formulations without subpixel refinement and without non-textured corner filter). For accuracy/robustness, experimental results for several real-world scenes are encouraging and show the feasibility of our algorithmic approach.

Keywords

Robust feature extraction Smart camera FPGA 3D reconstruction 

Supplementary material

11554_2017_701_MOESM1_ESM.mp4 (52.8 mb)
Supplementary material 1 (mp4 54054 KB)

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Instituto Nacional de Astrofísica Óptica y Electrónica (INAOE)PueblaMexico
  2. 2.Institut PascalUniversité Clermont AuvergneAubière, Clermont-FerrandFrance

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