转：基于Aforge的手势字符识别

cvchina — Thu, 29 Jul 2010 12:11:28 +0000

还是来自hellogv，呵呵。

Afroge我是第一次看到，孤陋寡闻了。下面是一点介绍。

AForge.NET is an open source C# framework designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence – image processing, neural networks, genetic algorithms, fuzzy logic, machine learning, robotics, etc.

The framework is comprised by the set of libraries and sample applications, which demonstrate their features:

AForge.Imaging – library with image processing routines and filters;

AForge.Vision – computer vision library;

AForge.Video – set of libraries for video processing;

AForge.Neuro – neural networks computation library;

AForge.Genetic – evolution programming library;

AForge.Fuzzy – fuzzy computations library;

AForge.Robotics – library providing support of some robotics kits;

AForge.MachineLearning – machine learning library;

etc.

我实现手势识别的原理很简单：捕捉运动物体+手写识别，把运动的物体的轨迹记录下来，然后通过手写识别引擎去搜索数据中最匹配的数据，从而知道“写”的是什么。目前常见的开源手写识别引擎有zinnia，wagomu 这些，不过小弟我比较业余，只把网上的比较常见的手写识别代码改进一下，只能识别字母和数字，真想通过摄像头隔空“手写”的朋友就要多花时间玩玩上面提到的几个开源手写类库了。

本文介绍的手写识别：先在一个固定大小的画板上，用鼠标画下某图形，输入该图形对应的字母，程序把画板上的字母特征点都保存下来特征数据库(相当于学习记忆)，然后再在画板上画出类似该字母的图形，程序就通过新画的特征点搜索特征数据库从而找出最类似的字母。

接下来贴出核心代码，详细的代码请到这里下载：http://download.csdn.net/source/2312865

GetBMPContext()是把画板中的图形的特征分析出来，Learn()是把特征与特定的字母/数字对应起来保存到数据库，Recognise()是把当前画板的图形特征从数据库中搜索，从而找出对应的字母/数字。

const int SCAN_GAP = 10;

private String GetBMPContext(Bitmap bmp)

{

Boolean bool1stScan = true;

int ax = 0, ay = 0, bx = 0, by = 0;

String result = “”;

for (int i = 1; i < bmp.Width; i = i + SCAN_GAP)

{

for (int j = 1; j < bmp.Height; j = j + SCAN_GAP)

{

if (bmp.GetPixel(i, j).ToArgb() == Color.Black.ToArgb())

{

if (bool1stScan == false)

{

if (i <= ax) ax = i;

if (i >= bx) bx = i;

if (j <= ay) ay = j;

if (j >= by) by = j;

}

else

{

bool1stScan = false;

ax = i;

bx = i;

ay = j;

by = j;

}

Bitmap bmp2 = new Bitmap(20, 20);

Graphics g2 = Graphics.FromImage((Image)bmp2);

g2.Clear(Color.White);

g2.DrawImage(bmp, new Rectangle(0, 0, bmp2.Width, bmp2.Height),

new Rectangle(0, 0, bmp.Width, bmp.Height), GraphicsUnit.Pixel);

g2.Dispose();

// pictureBox1.Image = bmp2;

int a = 0, b = 0;

for (int i = 0; i < bmp2.Width; i++)

{

for (int j = 0; j < bmp2.Height; j++)

{

if (bmp2.GetPixel(i, j).ToArgb() == Color.Black.ToArgb())

result = result + “0″;

else

result = result + “1″;

}

return result;

}

public void Learn(String name)

{

StreamWriter sw = new StreamWriter(fileName, true);

sw.WriteLine(name + ” ” + GetBMPContext(bmpDraw));

sw.Close();

}

public String Recognise()

{

String current = GetBMPContext(bmpDraw);

StreamReader sr = new StreamReader(fileName);

int max = 0;

String result = “”;

while (sr.EndOfStream == false)

{

String[] key = sr.ReadLine().Split(‘ ‘);

String name = key[0];

String data = key[1];

int match = 0;

for (int i = 0; i < current.Length; i++)

{

if (current[i] == data[i])

match++;

}

if (match >= max)

{

result = name;

max = match;

}

//Trace.WriteLine(result + “:” + match + “,” + max);

}

sr.Close();

return result;

}

Tags: aforge, gesture, ocr, 手势, 新闻, 轨迹识别

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转：基于Aforge的手势字符识别

增强视觉 | 计算机视觉增强现实 » 轨迹识别