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Lecture notes from university.
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     15   <title>Image processing</title>
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     17 
     18 <body>
     19   <div>Problems:</div>
     20   <div>
     21     <ol>
     22       <li>Acquired signals are often noisy</li>
     23       <li>Context information is often hidden</li>
     24     </ol>
     25     <div><br /></div>
     26   </div>
     27   <div>Below are options for image processing.</div>
     28   <div><br /></div>
     29   <div><a href="Point processing.html"">Point processing</a></div>
     30   <div><a href="Neighborhood processing.html"">Neighborhood processing</a></div>
     31   <div><a href="Morphological operations.html">Morphological operations</a></div>
     32   <div><br /></div>
     33   <div><span style="font-weight: bold;">Windowing</span></div>
     34   <div>Select a region of interest — user defined region within the image.</div>
     35   <div>Then crop (resize) the image.</div>
     36   <div><br /></div>
     37   <div><span style="font-family: &quot;Helvetica Neue&quot;; font-weight: bold;">Segmentation</span></div>
     38   <div><span style="font-family: &quot;Helvetica Neue&quot;;">Partitioning an image into separate objects, main vs background.</span></div>
     39   <div><span style="font-family: &quot;Helvetica Neue&quot;;">Can be done by:</span></div>
     40   <div>
     41     <ul>
     42       <li><span style="font-family: &quot;Helvetica Neue&quot;;">Edge detection</span></li>
     43       <ul>
     44         <li><span style="font-family: &quot;Helvetica Neue&quot;;">edge — local discontinuity in pixel value that exceeds given threshold</span></li>
     45         <li><span style="font-family: &quot;Helvetica Neue&quot;;">consists of creating binary image where non-background pixel values are object boundaries</span></li>
     46       </ul>
     47     </ul>
     48   </div>
     49   <blockquote style="margin: 0 0 0 40px; border: none; padding: 0px;">
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     52         <font face="Helvetica Neue"><img src="Image%20processing.resources/screenshot.png" height="245" width="467" /><br /></font>
     53       </div>
     54     </blockquote>
     55   </blockquote>
     56   <div>
     57     <ul>
     58       <ul>
     59         <li><span style="font-family: &quot;Helvetica Neue&quot;;">can be obtained by correlation with a kernel</span></li>
     60         <ul>
     61           <li><span style="font-family: &quot;Helvetica Neue&quot;;">Prewitt</span></li>
     62           <li><span style="font-family: &quot;Helvetica Neue&quot;;">Canny</span></li>
     63           <li><span style="font-family: &quot;Helvetica Neue&quot;;"> Sobel</span></li>
     64         </ul>
     65       </ul>
     66     </ul>
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     70       <div><img src="Image%20processing.resources/screenshot_2.png" height="292" width="474" /><br /></div>
     71     </blockquote>
     72   </blockquote>
     73   <div><br /></div>
     74   <div><br /></div>
     75   <div><br /></div>
     76   <div><br /></div>
     77   <div><span style="font-weight: bold;">BLOB analysis</span></div>
     78   <div>BLOB — binary large object (group of connected pixels in binary image)</div>
     79   <div>connectivity decides which pixels are neighbours (4-connectivity, 8 connectivity)</div>
     80   <div>set of allpixels which are connected to a given pixel is a connected component or BLOB</div>
     81   <div><br /></div>
     82   <div><img src="Image%20processing.resources/screenshot_1.png" height="107" width="367" /><br /></div>
     83   <div><br /></div>
     84   <div>extracting connected components is called labelling, each connected component is given a label.</div>
     85   <div>0 is background, then 1,2,3,…</div>
     86   <div>in MATLAB, <span style="font-family: &quot;Courier New&quot;;">bwlabel </span><span style="font-family: &quot;Helvetica Neue&quot;;">returns matrix with labels and number of BLOBs</span></div>
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