blocks|key|43229|text|我发现Christian+Graus关于Code+Project的系列文章很有用：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|43230|Image+Processing+for+Dummies+with+C#+and+GDI%2B+Part+1+-+Per+Pixel+Filters|offset|length|43231|Image+Processing+for+Dummies+with+C#+and+GDI%2B+Part+2+-+Convolution+Filters|43232|43233|Image+Processing+for+Dummies+with+C#+and+GDI%2B+Part+4+-+Bilinear+Filters+and+Resizing|43234|Image+Processing+for+Dummies+with+C#+and+GDI%2B+Part+5+-+Displacement+filters,+including+swirl|43235|Image+Processing+for+Dummies+with+C#+and+GDI%2B+Part+6+-+The+HSL+color+space|43236|entityMap|0|LINK|mutability|MUTABLE|url|http://www.codeproject.com/KB/GDI-plus/csharpgraphicfilters11.aspx|1|http://www.codeproject.com/KB/GDI-plus/csharpfilters.aspx|2|http://www.codeproject.com/KB/GDI-plus/imageprocessing4.aspx|3|http://www.codeproject.com/KB/GDI-plus/displacementfilters.aspx|4|http://www.codeproject.com/KB/GDI-plus/HSLColorSpace.aspx^0|0|0|20|0|0|0|22|1|0|0|0|2C|2|0|0|2K|3|0|0|22|4|0^^$0|@$1|2|3|4|5|6|7|14|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|15|8|@]|9|@$D|16|E|17|1|18]]|A|$]]|$1|F|3|G|5|6|7|19|8|@]|9|@$D|1A|E|1B|1|1C]]|A|$]]|$1|H|3|-4|5|6|7|1D|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|1E|8|@]|9|@$D|1F|E|1G|1|1H]]|A|$]]|$1|K|3|L|5|6|7|1I|8|@]|9|@$D|1J|E|1K|1|1L]]|A|$]]|$1|M|3|N|5|6|7|1M|8|@]|9|@$D|1N|E|1O|1|1P]]|A|$]]|$1|O|3|-4|5|6|7|1Q|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V]]|W|$5|R|S|T|A|$U|X]]|Y|$5|R|S|T|A|$U|Z]]|10|$5|R|S|T|A|$U|11]]|12|$5|R|S|T|A|$U|13]]]]

I found the series by Christian Graus on Code Project to be useful:

<a href="http://www.codeproject.com/KB/GDI-plus/csharpgraphicfilters11.aspx" rel="noreferrer">Image Processing for Dummies with C# and GDI+ Part 1 - Per Pixel Filters</a> 
<a href="http://www.codeproject.com/KB/GDI-plus/csharpfilters.aspx" rel="noreferrer">Image Processing for Dummies with C# and GDI+ Part 2 - Convolution Filters</a> 
<a href="http://www.codeproject.com/KB/GDI-plus/edge_detection.aspx" rel="noreferrer">Image Processing for Dummies with C# and GDI+ Part 3 - Edge Detection Filters</a> 
<a href="http://www.codeproject.com/KB/GDI-plus/imageprocessing4.aspx" rel="noreferrer">Image Processing for Dummies with C# and GDI+ Part 4 - Bilinear Filters and Resizing</a> 
<a href="http://www.codeproject.com/KB/GDI-plus/displacementfilters.aspx" rel="noreferrer">Image Processing for Dummies with C# and GDI+ Part 5 - Displacement filters, including swirl</a> 
<a href="http://www.codeproject.com/KB/GDI-plus/HSLColorSpace.aspx" rel="noreferrer">Image Processing for Dummies with C# and GDI+ Part 6 - The HSL color space</a>

blocks|key|1586662|text|我建议找一些好的计算机视觉课程幻灯片，比如这些|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|1586663|用于lecture+5:+Advanced+Image+Features+(ppt)|1586664|for边缘检测的|unordered-list-item|1586665|查看lecture+3:+Features+and+Linear+Filters和lecture+5:+Advanced+Image+Features+(ppt)|1586666|for高级分割技术查看lecture+12:+Segmentation+(ppt)+(如果您是计算机视觉新手，可能有点太高级了)|1586667|1586668|1586669|一般来说，我通过搜索大学网站上关于任何特定主题的powerpoint演示文稿来找到有趣的材料：|1586670|entityMap|0|LINK|mutability|MUTABLE|url|http://cs223b.stanford.edu/notes/CS223B-L5-AdvancedFeatures.ppt|1|http://cs223b.stanford.edu/notes/CS223B-L3-Features.ppt|2|3|http://cs223b.stanford.edu/notes/CS223B-L12-Segmentation.ppt^0|8|5|0|2|14|0|0|0|2|12|1|15|14|2|0|3|6|B|U|3|0|0|0|0^^$0|@$1|2|3|4|5|6|7|15|8|@$9|16|A|17|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|18|8|@]|D|@$9|19|A|1A|1|1B]]|E|$]]|$1|H|3|I|5|J|7|1C|8|@]|D|@]|E|$]]|$1|K|3|L|5|J|7|1D|8|@]|D|@$9|1E|A|1F|1|1G]|$9|1H|A|1I|1|1J]]|E|$]]|$1|M|3|N|5|J|7|1K|8|@$9|1L|A|1M|B|C]]|D|@$9|1N|A|1O|1|1P]]|E|$]]|$1|O|3|-4|5|6|7|1Q|8|@]|D|@]|E|$]]|$1|P|3|-4|5|6|7|1R|8|@]|D|@]|E|$]]|$1|Q|3|R|5|6|7|1S|8|@]|D|@]|E|$]]|$1|S|3|-4|5|6|7|1T|8|@]|D|@]|E|$]]]|T|$U|$5|V|W|X|E|$Y|Z]]|10|$5|V|W|X|E|$Y|11]]|12|$5|V|W|X|E|$Y|Z]]|13|$5|V|W|X|E|$Y|14]]]]

I would suggest looking for good computer vision course slides, such as these <a href="http://cs223b.stanford.edu/schedule.html" rel="noreferrer">Stanford one</a>:

<ul>
<li>for edge detection check out <a href="http://cs223b.stanford.edu/notes/CS223B-L3-Features.ppt" rel="noreferrer">lecture 3: Features and Linear Filters</a> and <a href="http://cs223b.stanford.edu/notes/CS223B-L5-AdvancedFeatures.ppt" rel="noreferrer">lecture 5: Advanced Image Features (ppt)</a></li>
<li>for advanced segmentation techniques check out <a href="http://cs223b.stanford.edu/notes/CS223B-L12-Segmentation.ppt" rel="noreferrer">lecture 12: Segmentation (ppt)</a> (perhaps a bit too advanced if you're new to computer vision)</li>
</ul>

In general I find interesting materials by googling university sites for powerpoint presentations on any given subject: <a href="http://www.google.com/search?q=computer+vision+filetype:ppt+site:edu" rel="noreferrer">computer vision site:edu filetype:ppt</a>

blocks|key|43415|text|您可能希望广泛使用OpenCv：http://opencv.willowgarage.com/wiki/Welcome|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|43416|您需要的许多算法已经在OpenCv中实现。因此，你的首要任务应该是尽可能多地学习计算机视觉，可能是从有关该主题的书籍中学习，而不是从在线资源中。你会发现在线资源是检查尖端研究或非常基础的技术的好地方，中间非常需要的介绍性材料通常会丢失。|43417|entityMap|0|LINK|mutability|MUTABLE|url|http://opencv.willowgarage.com/wiki/Welcome^0|G|17|0|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]]|C|$]]|$1|D|3|E|5|6|7|R|8|@]|9|@]|C|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]]]

You will probably want to make extensive use of OpenCv: <a href="http://opencv.willowgarage.com/wiki/Welcome" rel="nofollow noreferrer">http://opencv.willowgarage.com/wiki/Welcome</a>

Many of the algorithms that you need are already implemented in OpenCv. So your first priority should be to LEARN as much about computer vision as possible, probably from books on the topic not online resources. You will find that online resources are great places to check up on cutting edge research or extremely basic techniques, the inbetween introductory material that is very much needed is usually missing.

blocks|key|1447303|text|不久前，我为一个uni项目做了一些非常基本的边缘检测。我原型的算法是Laplace和Sobel。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1447304|这个页面为我提供了实现算法所需的大部分信息：|1447305|http://www.pages.drexel.edu/~weg22/edge.html|offset|length|1447306|我有一些C%2B%2B源代码，如果你感兴趣的话，这些源代码在过去可能有点可怕。|1447307|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|0|18|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|R|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|S|8|@]|9|@$F|T|G|U|1|V]]|A|$]]|$1|H|3|I|5|6|7|W|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|X|8|@]|9|@]|A|$]]]|K|$L|$5|M|N|O|A|$P|E]]]]

I did some very basic edge detection for a uni project a while back. The algorithms that I prototyped were Laplace and Sobel.

This is the page that got me most of the info I needed to implement the algorithm:

<a href="http://www.pages.drexel.edu/~weg22/edge.html" rel="nofollow noreferrer">http://www.pages.drexel.edu/~weg22/edge.html</a>

I have some C++ source code that might be a bit scary from back in the day if you are interested.

I am involved in a personal project which will require pretty extensive knowledge of edge detection and image segmentation/object recognition.

I know the importance of planning/understanding before writing code and with this in mind, what is the best place to start, to learn about these areas of computing? I am ideally looking for online articles/papers.

Thanks

Best articles to start learning about edge detection/image recognition

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我参与了一个个人项目，该项目需要相当广泛的边缘检测和图像分割/对象识别知识。我知道在编写代码之前规划/理解的重要性，考虑到这一点，从哪里开始学习这些计算领域的知识是最好的起点？理想情况下，我正在寻找在线文章/论文。谢谢

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