OpenCV中基于形状的模板匹配技术:超越Halcon的效率,支持C++ C#多语言环境下的32位与64位版本,高效创建模型模型(create-shape-model-xld)的实现方法 ,OpenC
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OpenCV中基于形状的模板匹配技术:超越Halcon的效率,支持C++ C#多语言环境下的32位与64位版本,高效创建模型模型(create_shape_model_xld)的实现方法。,OpenCV中基于形状的模板匹配技术:快速与Halcon相媲的C++与C#实现,模板匹配,基于形状的模板匹配,速度直逼halcon,openCV实现,C++ C#,32 64位,create_shape_model_xld,模板匹配; 基于形状的模板匹配; 速度直逼Halcon; OpenCV实现; C++与C#编程语言; 32与64位环境; create_shape_model_xld,OpenCV加速模板匹配:基于形状的快速算法,C++/C#双语言支持,32/64位兼容 <link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90401199/2/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90401199/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">基于形状的模板匹配<span class="ff2">:<span class="ff3">OpenCV<span class="_ _0"> </span></span></span>的<span class="_ _1"> </span><span class="ff3">C++</span>与<span class="_ _1"> </span><span class="ff3">C#</span>实现及性能分析</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">一<span class="ff4">、</span>引言</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">在图像处理和计算机视觉领域<span class="ff2">,</span>模板匹配是一项重要的技术<span class="ff4">。</span>它可以帮助我们快速<span class="ff4">、</span>准确地定位图像</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">中的特定区域或对象<span class="ff4">。</span>基于形状的模板匹配是模板匹配的一种<span class="ff2">,</span>它特别适用于对形状进行匹配<span class="ff2">,</span>如寻</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">找图像中的特定物体或区域<span class="ff4">。</span>本文将详细介绍基于形状的模板匹配的原理<span class="ff4">、<span class="ff3">OpenCV<span class="_ _0"> </span></span></span>的实现方法<span class="ff2">,</span>以</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">及<span class="_ _1"> </span><span class="ff3">C++</span>和<span class="_ _1"> </span><span class="ff3">C#</span>语言中的实现<span class="ff2">,</span>同时<span class="ff2">,</span>我们还将探讨其在<span class="_ _1"> </span><span class="ff3">32<span class="_ _0"> </span></span>位和<span class="_ _1"> </span><span class="ff3">64<span class="_ _0"> </span></span>位系统上的性能<span class="ff4">。</span></div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">二<span class="ff4">、</span>基于形状的模板匹配原理</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">基于形状的模板匹配是一种基于目标形状特征的方法<span class="ff4">。</span>它首先提取目标形状的特征<span class="ff2">,</span>然后在图像中搜</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">索与目标形状最相似的区域<span class="ff4">。</span>这种方法的优点是可以很好地处理图像的旋转<span class="ff4">、</span>缩放和变形<span class="ff2">,</span>因此<span class="ff2">,</span>它</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">在机器视觉<span class="ff4">、</span>医学图像分析等领域有着广泛的应用<span class="ff4">。</span></div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">三<span class="ff4">、<span class="ff3">OpenCV<span class="_ _0"> </span></span></span>中的基于形状的模板匹配</div><div class="t m0 x1 h2 yc ff3 fs0 fc0 sc0 ls0 ws0">OpenCV<span class="_ _0"> </span><span class="ff1">是一个强大的计算机视觉库<span class="ff2">,</span>它提供了丰富的模板匹配函数<span class="ff4">。</span>在<span class="_ _1"> </span></span>OpenCV<span class="_ _0"> </span><span class="ff1">中<span class="ff2">,</span>我们可以使用</span></div><div class="t m0 x1 h2 yd ff3 fs0 fc0 sc0 ls0 ws0">`createShapeModelXLD`<span class="ff1">函数来创建形状模型<span class="ff2">,</span>然后使用</span>`matchShape`<span class="ff1">函数来进行形状匹配<span class="ff4">。</span></span></div><div class="t m0 x1 h3 ye ff3 fs0 fc0 sc0 ls0 ws0">```cpp</div><div class="t m0 x1 h2 yf ff3 fs0 fc0 sc0 ls0 ws0">// <span class="ff1">假设我们已经有了训练好的形状模型</span></div><div class="t m0 x1 h3 y10 ff3 fs0 fc0 sc0 ls0 ws0">Ptr<ShapeModel> shapeModel = createShapeModel(ShapeModel::create("subPix", </div><div class="t m0 x1 h3 y11 ff3 fs0 fc0 sc0 ls0 ws0">0, 0, 5, 8, 0.01, 1));</div><div class="t m0 x1 h2 y12 ff3 fs0 fc0 sc0 ls0 ws0">// <span class="ff1">假设我们已经有了一个目标图像和一个模板图像</span></div><div class="t m0 x1 h3 y13 ff3 fs0 fc0 sc0 ls0 ws0">Mat targetImage, templateImage;</div><div class="t m0 x1 h2 y14 ff3 fs0 fc0 sc0 ls0 ws0">// <span class="ff1">我们可以使用<span class="_ _1"> </span></span>matchShape<span class="_ _0"> </span><span class="ff1">函数进行形状匹配</span></div><div class="t m0 x1 h3 y15 ff3 fs0 fc0 sc0 ls0 ws0">double best_score = 0;</div><div class="t m0 x1 h3 y16 ff3 fs0 fc0 sc0 ls0 ws0">Point best_loc;</div><div class="t m0 x1 h3 y17 ff3 fs0 fc0 sc0 ls0 ws0">matchShape(targetImage, templateImage, shapeModel,</div><div class="t m0 x2 h3 y18 ff3 fs0 fc0 sc0 ls0 ws0">&best_score,</div><div class="t m0 x2 h3 y19 ff3 fs0 fc0 sc0 ls0 ws0">&best_loc,</div><div class="t m0 x2 h3 y1a ff3 fs0 fc0 sc0 ls0 ws0">ShapeMatcher::UPRIGHT,</div><div class="t m0 x2 h3 y1b ff3 fs0 fc0 sc0 ls0 ws0">ShapeMatcher::MAT_CNT);</div><div class="t m0 x1 h2 y1c ff3 fs0 fc0 sc0 ls0 ws0">// best_score<span class="_ _0"> </span><span class="ff1">是匹配得分<span class="ff2">,</span></span>best_loc<span class="_ _0"> </span><span class="ff1">是匹配位置</span></div><div class="t m0 x1 h3 y1d ff3 fs0 fc0 sc0 ls0 ws0">```</div><div class="t m0 x1 h2 y1e ff1 fs0 fc0 sc0 ls0 ws0">四<span class="ff4">、<span class="ff3">C++</span></span>与<span class="_ _1"> </span><span class="ff3">C#</span>实现</div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>