An optimal linear operator for step edge detection
CVGIP: Graphical Models and Image Processing
Logic Synthesis for Field-Programmable Gate Arrays
Logic Synthesis for Field-Programmable Gate Arrays
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Evolutionary consequences of coevolving targets
Evolutionary Computation
Image Filter Design with Evolvable Hardware
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation
Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation
Mixed constrained image filter design using particle swarm optimization
Artificial Life and Robotics
Fault-tolerant image filter design using particle swarm optimization
Artificial Life and Robotics
An evolvable image filter: experimental evaluation of a complete hardware implementation in FPGA
ICES'05 Proceedings of the 6th international conference on Evolvable Systems: from Biology to Hardware
| Hi-index | 0.00 |
In this paper, we investigate a unique method of inventing linear edge enhancement operators using evolution and reconfigurable hardware. We show that the technique is motivated by the desire for a totally automated object recognition system. We show that an important step in automating object recognition is to provide flexible means to smooth images, making features more obvious and reducing interference. Next we demonstrate a technique for building an edge enhancement operator using evolutionary methods, implementing and testing each generation using the Xilinx 6200 family FPGA. Finally, we present the results and conclude by mentioning some areas of further investigation.