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algorithme reconnaissance de plaque mineralogique
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内容介绍
<html xmlns="http://www.w3.org/1999/xhtml"> <head> <meta charset="utf-8"> <meta name="generator" content="pdf2htmlEX"> <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> <link rel="stylesheet" href="https://static.pudn.com/base/css/base.min.css"> <link rel="stylesheet" href="https://static.pudn.com/base/css/fancy.min.css"> <link rel="stylesheet" href="https://static.pudn.com/prod/directory_preview_static/6252987674bc5c0105d72e33/raw.css"> <script src="https://static.pudn.com/base/js/compatibility.min.js"></script> <script src="https://static.pudn.com/base/js/pdf2htmlEX.min.js"></script> <script> try{ pdf2htmlEX.defaultViewer = new pdf2htmlEX.Viewer({}); }catch(e){} </script> <title></title> </head> <body> <div id="sidebar" style="display: none"> <div id="outline"> </div> </div> <div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/6252987674bc5c0105d72e33/bg1.jpg"><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">License Plate Location Recognition based on Multiagent System </div><div class="t m0 x2 h3 y2 ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x2 h3 y3 ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x3 h3 y4 ff2 fs1 fc0 sc0 ls2 ws2">M. Ebrahimi </div><div class="t m0 x4 h4 y5 ff3 fs1 fc0 sc0 ls2 ws2">Department of </div><div class="t m0 x5 h4 y6 ff3 fs1 fc0 sc0 ls3 ws1">Majlesi </div><div class="t m0 x6 h4 y7 ff3 fs1 fc0 sc0 ls2 ws2">Azad University </div><div class="t m0 x7 h4 y8 ff3 fs1 fc0 sc0 ls4 ws1">hoo_Ebrahimi@y</div><div class="t m0 x8 h4 y9 ff3 fs1 fc0 sc0 ls5 ws1">ahoo.com </div><div class="t m0 x9 h3 ya ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x9 h3 yb ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 xa h3 y4 ff2 fs1 fc0 sc0 ls6 ws3">S. Ildarabadi </div><div class="t m0 xb h4 y5 ff3 fs1 fc0 sc0 ls2 ws2">Department of </div><div class="t m0 xc h4 y6 ff3 fs1 fc0 sc0 ls4 ws1">Sepahan </div><div class="t m0 xd h4 y7 ff3 fs1 fc0 sc0 ls7 ws1">University </div><div class="t m0 xe h4 y8 ff3 fs1 fc0 sc0 ls8 ws1">sedigheh_ildarab</div><div class="t m0 xf h4 y9 ff3 fs1 fc0 sc0 ls4 ws1">adi@yahoo.com </div><div class="t m0 x10 h4 yc ff3 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x10 h4 yd ff3 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x11 h3 y4 ff2 fs1 fc0 sc0 ls4 ws4">R. Monsefi </div><div class="t m0 x12 h4 y5 ff3 fs1 fc0 sc0 ls6 ws3">Faculty of </div><div class="t m0 x13 h4 y6 ff3 fs1 fc0 sc0 ls8 ws1">engineering </div><div class="t m0 x14 h4 y7 ff3 fs1 fc0 sc0 ls9 ws1">Ferdowsi </div><div class="t m0 x12 h4 y8 ff3 fs1 fc0 sc0 ls7 ws1">University </div><div class="t m0 x15 h4 y9 ff3 fs1 fc0 sc0 ls2 ws1">rmonsefi@ferdow</div><div class="t m0 x16 h4 yc ff3 fs1 fc0 sc0 lsa ws1">si.um.ac.ir<span class="ff2 fs2 lsb"> </span></div><div class="t m0 x17 h5 ye ff2 fs2 fc0 sc0 ls1 ws1"> </div><div class="t m0 x18 h3 y4 ff2 fs1 fc0 sc0 ls9 ws5">M. R. Akbarzadeh<span class="fs2 ls1 ws1"> </span></div><div class="t m0 x19 h6 yf ff3 fs2 fc0 sc0 ls1 ws1"> </div><div class="t m0 x1a h4 y5 ff3 fs1 fc0 sc0 ls6 ws3">Faculty of </div><div class="t m0 x1b h4 y6 ff3 fs1 fc0 sc0 ls8 ws1">engineering </div><div class="t m0 x1c h4 y7 ff3 fs1 fc0 sc0 ls9 ws1">Ferdowsi </div><div class="t m0 x19 h4 y8 ff3 fs1 fc0 sc0 ls7 ws1">University </div><div class="t m0 x18 h4 y9 ff3 fs1 fc0 sc0 ls8 ws1">akbarzadeh@ieee.</div><div class="t m0 x1d h4 yc ff3 fs1 fc0 sc0 lsa ws1">org</div><div class="t m0 x2 h3 y10 ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x1e h7 y11 ff1 fs1 fc0 sc0 lsc ws1">Abstract </div><div class="t m0 x1e h8 y12 ff3 fs3 fc0 sc0 ls1 ws1"> </div><div class="t m0 x1e h8 y13 ff3 fs3 fc0 sc0 lsd ws6">A novel approach is proposed for automatic license <span class="_ _0"></span><span class="lse ws7">plate location recognition <span class="lsf ws8">based on a fusion Gabor and </span></span></div><div class="t m0 x1e h8 y14 ff3 fs3 fc0 sc0 ls10 ws9">Multiple Interlacing in a multiagent <span class="ls11 wsa">configuration. License Plate Recogn<span class="_ _0"></span><span class="ls12 wsb">ition Systems based on machine vision </span></span></div><div class="t m0 x1e h8 y15 ff3 fs3 fc0 sc0 ls13 wsc">solely need to increasing speed and accuracy in real<span class="_ _0"></span> applications (i<span class="_ _0"></span>.e. atmospheric dark and glare)<span class="_ _0"></span>. </div><div class="t m0 x1e h8 y16 ff3 fs3 fc0 sc0 ls14 wsd">In this model, the images that Speedy-MI agent has not been able to detect<span class="_ _0"></span>, is delegated to the Accurate<span class="_ _0"></span>-Gabor </div><div class="t m0 x1e h8 y17 ff3 fs3 fc0 sc0 ls15 wse">agent by the Moderator agent. The proposed <span class="_ _1"></span>model is implemented and test<span class="_ _0"></span>ed on 200 images that is toke f<span class="_ _0"></span>rom </div><div class="t m0 x1e h8 y18 ff3 fs3 fc0 sc0 ls11 wsf">Tehran Control Traffic Apartment. The results show <span class="ls16 ws10">that overall speed and accu<span class="ls17 ws11">racy has been improved. </span></span></div><div class="t m0 x2 h3 y19 ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x2 h3 y1a ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x1e h3 y1b ff1 fs1 fc0 sc0 ls6 ws1">Keywords: <span class="_"> </span><span class="ff2 ws12">License Plate Location (LPL), Multiagent<span class="ls18 ws13"> System<span class="_ _0"></span>s, Multiple Interlacing, Gabor </span></span></div><div class="t m0 x1e h3 y1c ff2 fs1 fc0 sc0 lsc ws1">Transformation. </div><div class="t m0 x1e h3 y1d ff2 fs1 fc0 sc0 ls1 ws1"> </div><div class="t m0 x1f h9 y1e ff2 fs3 fc0 sc0 ls1 ws1"> </div><div class="t m0 x1f h7 y1f ff1 fs1 fc0 sc0 ls9 ws5">1. Introduction </div><div class="t m0 x1f h9 y20 ff2 fs3 fc0 sc0 ls1 ws1"> </div><div class="t m0 x7 h9 y21 ff2 fs3 fc0 sc0 ls19 ws14">During the past few years, intelligen<span class="_ _1"></span>t transportation </div><div class="t m0 x1f h9 y22 ff2 fs3 fc0 sc0 ls12 ws15">systems (ITSs) have had a wide i<span class="_ _0"></span>mpact in people&#8217;s <span class="_ _0"></span>life as </div><div class="t m0 x1f h9 y23 ff2 fs3 fc0 sc0 ls14 ws16">their scope is to improve transportat<span class="_ _0"></span>ion safety and </div><div class="t m0 x1f h9 y24 ff2 fs3 fc0 sc0 ls16 ws17">mobility and to enhance productivity through the use of </div><div class="t m0 x1f h9 y25 ff2 fs3 fc0 sc0 ls10 ws18">advanced technologies. We will <span class="ws19">review 4 types of license </span></div><div class="t m0 x1f h9 y26 ff2 fs3 fc0 sc0 ls1a ws1a">plate location recogn<span class="_ _1"></span>ition algorithms in this sectio<span class="_ _1"></span>n. </div><div class="t m0 x7 h9 y27 ff2 fs3 fc0 sc0 ls14 ws1b">I) As far as extraction of the plat<span class="_ _0"></span>e region is <span class="_ _0"></span>concerned, </div><div class="t m0 x1f h9 y28 ff2 fs3 fc0 sc0 ls13 ws1c">techniques based upon combinat<span class="_ _0"></span>ions of edge stati<span class="_ _0"></span>stics </div><div class="t m0 x1f h9 y29 ff2 fs3 fc0 sc0 ls15 ws1d">and mathem<span class="_ _0"></span>atical m<span class="_ _0"></span>orphology [1-4] feat<span class="_ _0"></span>ured very good </div><div class="t m0 x1f h9 y2a ff2 fs3 fc0 sc0 ls1b ws1e">results. In these m<span class="_ _0"></span>ethods, gradient <span class="_ _0"></span>magnit<span class="_ _0"></span>ude and their </div><div class="t m0 x1f h9 y2b ff2 fs3 fc0 sc0 ls1c ws1f">local variance in an image ar<span class="ls16 ws20">e computed. They are based </span></div><div class="t m0 x1f h9 y2c ff2 fs3 fc0 sc0 ls17 ws21">on the property that the brightness change in the license </div><div class="t m0 x1f h9 y2d ff2 fs3 fc0 sc0 ls1b ws22">plate region is more rem<span class="_ _0"></span>arkable and more frequent t<span class="_ _0"></span>han </div><div class="t m0 x1f h9 y2e ff2 fs3 fc0 sc0 ls15 ws23">otherwise. Block-based processing i<span class="_ _0"></span>s also supported [5]<span class="_ _0"></span>. </div><div class="t m0 x1f h9 y2f ff2 fs3 fc0 sc0 ls1d ws24">Then, regions with a high edge magnitude and hi<span class="_ _0"></span>gh edge </div><div class="t m0 x1f h9 y30 ff2 fs3 fc0 sc0 ls10 ws25">variance are identified as po<span class="ls1 ws26">ssible license plate regions. </span></div><div class="t m0 x1f h9 y31 ff2 fs3 fc0 sc0 ls14 ws27">Since this m<span class="_ _0"></span>ethod does not depend on the edge of license </div><div class="t m0 x1f h9 y32 ff2 fs3 fc0 sc0 ls13 ws28">plate boundary, it can be applied to an im<span class="_ _0"></span>age with </div><div class="t m0 x20 h9 y33 ff2 fs3 fc0 sc0 ls13 ws29">unclear license plate boundary and can be im<span class="_ _0"></span>plem<span class="_ _0"></span>ented </div><div class="t m0 x20 h9 y34 ff2 fs3 fc0 sc0 ls1e ws2a">simply and fast<span class="_ _0"></span>. A disadvantage is that <span class="_ _0"></span>edge-based </div><div class="t m0 x20 h9 y35 ff2 fs3 fc0 sc0 ls14 ws2b">methods alone can hardl<span class="_ _0"></span>y be applied to com<span class="_ _0"></span>plex im<span class="_ _0"></span>ages, </div><div class="t m0 x20 h9 y36 ff2 fs3 fc0 sc0 ls1f ws2c">since they are too sensitiv<span class="_ _1"></span>e to unwanted edg<span class="_ _1"></span>es, which </div><div class="t m0 x20 h9 y37 ff2 fs3 fc0 sc0 ls20 ws2d">may al<span class="_ _0"></span>so show high edge magnit<span class="_ _0"></span>ude or variance (e.g., <span class="_ _0"></span>the </div><div class="t m0 x20 h9 y38 ff2 fs3 fc0 sc0 ls1b ws2e">radiator region in the front vi<span class="_ _0"></span>ew of the vehicle). <span class="_ _0"></span>In spite </div><div class="t m0 x20 h9 y39 ff2 fs3 fc0 sc0 ls13 ws2f">of this, when combined with m<span class="_ _0"></span>orphological steps that </div><div class="t m0 x20 h9 y3a ff2 fs3 fc0 sc0 ls10 ws30">eliminate unwanted edges in the processed images. </div><div class="t m0 x21 h9 y3b ff2 fs3 fc0 sc0 ls13 ws31">II) In [6], a method is developed to scan a vehicl<span class="_ _0"></span>e </div><div class="t m0 x20 h9 y3c ff2 fs3 fc0 sc0 ls13 ws32">image wit<span class="_ _0"></span>h N row distance and count the existent<span class="_ _0"></span> edges. </div><div class="t m0 x20 h9 y3d ff2 fs3 fc0 sc0 ls13 ws33">If the number of the edges is great<span class="_ _0"></span>er than a threshol<span class="_ _0"></span>d </div><div class="t m0 x20 h9 y3e ff2 fs3 fc0 sc0 ls21 ws34">value, this manifests the presen<span class="ls22 ws35">ce <span class="_ _1"></span>of a plate. If in the first </span></div><div class="t m0 x20 h9 y3f ff2 fs3 fc0 sc0 ls13 ws36">scanning process the plate is not found, t<span class="_ _0"></span>hen the </div><div class="t m0 x20 h9 y40 ff2 fs3 fc0 sc0 ls15 ws37">algorithm i<span class="_ _0"></span>s repeated, reducing the threshold <span class="_ _0"></span>for counting </div><div class="t m0 x20 h9 y41 ff2 fs3 fc0 sc0 ls17 ws11">edges. The method features very<span class="_ _0"></span> fast execution tim<span class="_ _0"></span>es as it </div><div class="t m0 x20 h9 y42 ff2 fs3 fc0 sc0 ls1e ws38">scans some rows of the im<span class="_ _0"></span>age. Nonetheless, <span class="_ _0"></span>this m<span class="_ _0"></span>ethod </div><div class="t m0 x20 h9 y43 ff2 fs3 fc0 sc0 ls23 ws39">is extremely simple to locat<span class="ls24 ws3a">e license plates in several </span></div><div class="t m0 x20 h9 y44 ff2 fs3 fc0 sc0 ls10 ws3b">scenarios, and moreover, it is not size or <span class="_ _0"></span>distance </div><div class="t m0 x20 h9 y45 ff2 fs3 fc0 sc0 ls20 ws3c">independent. </div><div class="t m0 x21 h9 y46 ff2 fs3 fc0 sc0 lsd ws3d">III) Fuzzy logic has been applied to the problem <span class="_ _0"></span>of </div><div class="t m0 x20 h9 y47 ff2 fs3 fc0 sc0 ls22 ws3e">locating license plates [7-9<span class="ls1e ws3f">]. The authors ma<span class="_ _0"></span>de some </span></div><div class="c x22 y48 w2 ha"><div class="t m0 x0 hb y49 ff4 fs4 fc0 sc0 ls1 ws1">5th Iranian Conference on Machine Vision and Image Processing, November 4-6, 2008</div></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div> </body> </html>
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