A　new　recognition　method　of　vehicle　license　plates　based　on　neural　network　is　presented　in　this　paper.　For　the　Back　Propagation　(BP)　neural　network　often　trap　into　the　local　minimum　in　the　training　process,　a　Genetic　Neural　Network　(GNN),　GABP　was　constructed　by　combining　the　Genetic　Algorithm　(GA)　with　BP　neural　network.　The　training　of　the　GABP　neural　network　was　finished　in　two　steps.　The　GA　was　firstly　used　to　make　a　thorough　searching　in　the　global　space　for　the　weights　and　thresholds　of　the　neural　network,　which　can　ensure　they　fall　into　the　neighborhood　of　global　optimal　solution.　Then,　in　order　to　improve　the　convergence　precision,　the　gradient　method　was　used　to　finely　train　the　network　and　find　the　global　optimum　or　second-best　solution　with　good　performance.　On　the　other　side,　feature　extraction　is　also　important　for　improving　the　recognition　rate　of　the　network.　So　both　the　structure　features　and　the　statistic　features　are　used　in　this　paper,　which　include　mesh　feature,　direction　line　element　feature　and　Zernike　moments　feature.　Experimental　results　show　that　the　proposed　method　can　save　the　time　of　training　network　and　achieve　a　highly　recognition　rate.　©　2010　IEEE.