A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture

<table>Flowchart of developed system. The index <svg height="11.4625" id="M30" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 4.7624998 11.4625" width="4.7624998" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,11.2)"><path d="M244 607q0 -25 -15.5 -43t-37.5 -18q-19 0 -32 13t-13 35q0 21 15 41t39 20q20 0 32 -14t12 -34zM222 91q-29 -33 -79 -68t-75 -35q-13 0 -19 7.5t-6 31t10 65.5l62 253q5 26 -1 26q-21 0 -72 -43l-13 24q43 40 91 68t71 28q30 0 10 -78l-71 -274q-8 -30 3 -30
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</svg> refers to an individual in the population. The reproduction rate is pr, the crossover rate is pc, and the mutation rate is pm. The goal image can be created using an editor program or a processing program.</table>

International Journal of Reconfigurable Computing

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Figure 1

Figure 1: A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture 