Fuzzy logic-based embedded system for video de-interlacing

Abstract

Video de-interlacing algorithms perform a crucial task in video processing. Despite these algorithms are developed using software implementations, their implementations in hardware are required to achieve real-time operation. This paper describes the development of an embedded system for video de-interlacing. The algorithm for video de-interlacing uses three fuzzy logic-based systems to tackle three relevant features in video sequences: motion, edges, and picture repetition. The proposed strategy implements the algorithm as a hardware IP core on a FPGA-based embedded system. The paper details the proposed architecture and the design methodology to develop it. The resulting embedded system is verified on a FPGA development board and it is able to de-interlace in real-time.

Edge-adaptive spatial video de-interlacing algorithms based on fuzzy logic

“…A hardware demonstrator was developed on a medium-size FPGA to validate real-time implementation with HDTV resolution (30 frames/sec). This work was recently published by Brox et al [25]. …”

Neuro-fuzzy techniques to optimize an FPGA embedded controller for robot navigation

“…The continuous evolution of programmable devices has increased the use of FPGAs as platforms for the development of fuzzy systems [12]- [19]. Some of these FPGA implementations of fuzzy controllers are used to control autonomous mobile robots [16]- [19].…”