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<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/6277ec1177d3727348ec50d2/bg1.jpg"><div class="c x0 y1 w2 h2"><div class="t m0 x1 h3 y2 ff1 fs0 fc0 sc0 ls0 ws0">边缘检测</div><div class="t m0 x2 h4 y3 ff1 fs1 fc0 sc1 ls0 ws0">科技名词定义</div><div class="t m0 x3 h5 y4 ff1 fs2 fc1 sc0 ls0 ws0">中文名称:</div><div class="t m0 x4 h5 y5 ff1 fs2 fc0 sc0 ls0 ws0">边缘检测</div><div class="t m0 x3 h5 y6 ff1 fs2 fc1 sc0 ls0 ws0">英文名称:</div><div class="t m0 x4 h6 y7 ff2 fs2 fc0 sc0 ls0 ws0">edge detection </div><div class="t m0 x5 h5 y8 ff1 fs2 fc1 sc0 ls0 ws0">定义:</div><div class="t m0 x4 h5 y9 ff1 fs2 fc0 sc0 ls0 ws0">使用数学方法提取图像像元中具有亮度值<span class="ff2">(</span>灰度<span class="ff2">)</span>空间方向梯度大的边、线特征的过程。 </div><div class="t m0 x3 h5 ya ff1 fs2 fc1 sc0 ls0 ws0">应用学科:</div><div class="t m0 x4 h5 yb ff1 fs2 fc2 sc0 ls0 ws0">测绘学<span class="fc0">(一级学科);</span>摄影测量与遥感学<span class="fc0">(二级学科) </span></div><div class="t m0 x1 h4 yc ff1 fs1 fc0 sc0 ls0 ws0">以上内容由<span class="fc2">全国科学技术名词审定委员会</span>审定公布</div><div class="t m0 x1 h5 yd ff1 fs2 fc0 sc1 ls0 ws0">百科名片</div><div class="t m0 x1 h4 ye ff1 fs1 fc0 sc0 ls0 ws0">边缘检测是<span class="fc2">图像处理</span>和<span class="fc2">计算机视觉</span>中的基本问题,边缘检测的目的是标识数字</div><div class="t m0 x1 h4 yf ff1 fs1 fc0 sc0 ls0 ws0">图像中亮度变化明显的点。图像属性中的显著变化通常反映了属性的重要事件</div><div class="t m0 x1 h4 y10 ff1 fs1 fc0 sc0 ls0 ws0">和变化。 这些包括(<span class="ff2">i</span>)深度上的不连续、(<span class="ff2">ii</span>)表面方向不连续、(<span class="ff2">iii</span>)物质</div><div class="t m0 x1 h4 y11 ff1 fs1 fc0 sc0 ls0 ws0">属性变化和(<span class="ff2">iv</span>)场景照明变化。 边缘检测是图像处理和<span class="fc2">计算机视觉</span>中,尤其</div><div class="t m0 x1 h4 y12 ff1 fs1 fc0 sc0 ls0 ws0">是<span class="fc2">特征提取</span>中的一个研究领域。</div><div class="t m0 x1 h4 y13 ff1 fs1 fc0 sc0 ls0 ws0">目录</div><div class="t m0 x4 h4 y14 ff1 fs1 fc2 sc0 ls0 ws0">简介<span class="fc0"> </span></div><div class="t m0 x4 h4 y15 ff1 fs1 fc2 sc0 ls0 ws0">属性<span class="fc0"> </span></div><div class="t m0 x4 h4 y16 ff1 fs1 fc2 sc0 ls0 ws0">简单模型<span class="fc0"> </span></div><div class="t m0 x4 h4 y17 ff1 fs1 fc2 sc0 ls0 ws0">检测边缘<span class="fc0"> </span></div><div class="t m0 x4 h4 y18 ff1 fs1 fc2 sc0 ls0 ws0">阈值确定<span class="fc0"> </span></div><div class="t m0 x4 h4 y19 ff1 fs1 fc2 sc0 ls0 ws0">边缘检测算子</div><div class="t m0 x6 h4 y1a ff1 fs1 fc2 sc2 ls0 ws0">编辑本段<span class="fc0 sc1">简介</span></div><div class="t m0 x1 h4 y1b ff1 fs1 fc0 sc0 ls0 ws0">图像边缘检测大幅度地减少了数据量,并且剔除了可以认为不相关的信息,保</div><div class="t m0 x1 h4 y1c ff1 fs1 fc0 sc0 ls0 ws0">留了图像重要的结构属性。有许多方法用于边缘检测,它们的绝大部分可以划</div><div class="t m0 x1 h4 y1d ff1 fs1 fc0 sc0 ls0 ws0">分为两类:基于查找一类和基于零穿越的一类。基于查找的方法通过寻找图像</div><div class="t m0 x1 h4 y1e ff1 fs1 fc0 sc0 ls0 ws0">一阶导数中的最大和最小值来检测边界,通常是将边界定位在梯度最大的方向。</div><div class="t m0 x1 h4 y1f ff1 fs1 fc0 sc0 ls0 ws0">基于零穿越的方法通过寻找图像二阶导数零穿越来寻找边界,通常是</div><div class="t m0 x1 h4 y20 ff2 fs1 fc0 sc0 ls0 ws0">Laplacian<span class="_ _0"> </span><span class="ff1">过零点或者非线性<span class="fc2">差分</span>表示的过零点。</span></div><div class="t m0 x1 h4 y21 ff1 fs1 fc2 sc2 ls0 ws0">编辑本段<span class="fc0 sc1">属性</span></div><div class="t m0 x1 h4 y22 ff1 fs1 fc0 sc0 ls0 ws0">边缘可能与<span class="fc2">视角</span>有关—— 也就是说边缘可能随着视角不同而变化,典型地反映</div><div class="t m0 x1 h4 y23 ff1 fs1 fc0 sc0 ls0 ws0">在场景、物体的几何形状一个将另一个遮挡起来,也可能与视角无关——这通</div></div><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a><a class="l" rel='nofollow' onclick='return false;'><div class="d m1"></div></a></div><div class="pi" data-data='{"ctm":[1.611850,0.000000,0.000000,1.611850,0.000000,0.000000]}'></div></div>
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