1.vb 部分截屏之后识别上的图片文字
vb 部分截屏之后识别上的文字
主要是先要将转换为字节数组
'存放格式为(*, *, *),从左下角开始:
'第一维:0-蓝色分量,1-绿色分量,2-红色分量,
'第二维:列；第三维:行
全部步骤如下
1、用DibGet获取数据
2、数字识别用ColorToBlackAndWhite（或ColorToGray+OtsuColorToBlackAndWhite）将数据转换为黑白数据
3、源码用DibPut将数据恢复到一个PictureBox中
4、图片无源码和有源码的区别截取各个数字到单独的数字识别PictureBox中
5、将数字转换为数据，源码支付宝 源码并与标准数据（0-9）对比，图片相似度最高的数字识别为准（比如与1的相似度为%，与2的源码相似度为%，则此数字为2）
有问题Hi
'图像输出的图片过程:
Public Sub DIBPut(ByVal IdDestination As Long, ByRef ImageData() As Byte)
Dim LineBytes As Long
Dim Width As Long, Height As Long
Width = UBound(ImageData, 2) + 1
Height = UBound(ImageData, 3) + 1
On Error GoTo ErrLine
Done = False
With biBitInfo.bmiHeader
.biWidth = Width
.biHeight = Height
LineBytes = ((Width * Bits + ) And &HFFFFFFE0) \ 8
.biSizeImage = LineBytes * Height
End With
SetDIBitsToDevice IdDestination, 0, 0, Width, Height, 0, 0, 0, Height, ImageData(0, 0, 0), biBitInfo, 0
Done = True
Exit Sub
ErrLine:
MsgBox Err.Description
End Sub
'灰度处理SrcData(0 to 2, 0 to 宽度-1, 0 to 高度-1)
Public Sub ColorToGray(ByRef SrcData() As Byte, ByRef DestData() As Byte, _
Optional Left As Long = -1, Optional Top As Long = -1, _
Optional Right As Long = -1, Optional Bottom As Long = -1)
Dim i As Long, j As Long, k As Long
Dim red As Byte, green As Byte, blue As Byte
Dim Color As Long, newcolor As Long
Dim Width As Long, Height As Long
Width = UBound(SrcData, 2) + 1
Height = UBound(SrcData, 3) + 1
If Left = -1 Then Left = 0
If Top = -1 Then Top = 0
If Right = -1 Then Right = Width - 1
If Bottom = -1 Then Bottom = Height - 1
For j = Left To Right
For k = Height - Bottom - 1 To Height - Top - 1
blue = SrcData(0, j, k)
green = SrcData(1, j, k)
red = SrcData(2, j, k)
newcolor = CLng(0. * CDbl(red) + 0. * CDbl(green) + 0. * CDbl(blue)) '
newcolor = newcolor *
red = newcolor Mod
green = newcolor / Mod '( * RValue + * GValue + * BValue) /
blue = newcolor / /
DestData(0, j, k) = blue
DestData(1, j, k) = green
DestData(2, j, k) = red
Next
Next
End Sub
'黑白处理DestData(0 to 2, 0 to 宽度-1, 0 to 高度-1)
'最下面两行总是无法参与变换只好将采集的区域向下多延伸2个像素
Public Sub ColorToBlackAndWhite(ByRef SrcData() As Byte, ByRef DestData() As Byte)
Dim i As Long, j As Long, k As Long
Dim red As Byte, green As Byte, blue As Byte
Dim Color As Long, newcolor As Long
Dim Width As Long, Height As Long
Width = UBound(SrcData, 2) + 1
Height = UBound(SrcData, 3) + 1
For j = 0 To Width - 1
For k = 0 To Height - 1
blue = SrcData(0, j, k)
green = SrcData(1, j, k)
red = SrcData(2, j, k)
newcolor = CLng(0.3 * CDbl(red) + 0. * CDbl(green) + 0. * CDbl(blue))
' newcolor = CLng(0. * CDbl(red) + 0.5 * CDbl(green) + 0. * CDbl(blue))
If newcolor > Then newcolor = Else newcolor = 0
red = newcolor
green = newcolor
blue = newcolor
DestData(0, j, k) = blue
DestData(1, j, k) = green
DestData(2, j, k) = red
Next
Next
End Sub
'黑白处理DestData(0 to 2, 0 to 宽度-1, 0 to 高度-1)
'最下面两行总是无法参与变换只好将采集的区域向下多延伸2个像素
'OSTU算法可以说是自适应计算单阈值（用来转换灰度图像为二值图像）的简单高效方法。
' OTSU年提出的数字识别最大类间方差法以其计算简单、稳定有效，源码一直广为使用。图片支付宝源码
Public Sub OtsuColorToBlackAndWhite(ByRef SrcData() As Byte,数字识别 ByRef DestData() As Byte)
On Error Resume Next
Dim i As Long, j As Long, k As Long
Dim red As Byte, green As Byte, blue As Byte
Dim Color As Long, newcolor As Long
Dim Width As Long, Height As Long
Dim AllSum As Long, SumSmall As Long, SumBig As Long, PartSum As Long
Dim AllPixelNumber As Integer, PixelNumberSmall As Long, PixelNumberBig As Long
Dim ProbabilitySmall As Double, ProbabilityBig As Double, Probability As Double, MaxValue As Double
Dim BmpData() As Byte, Threshold As Byte
Dim Histgram() As Integer '图像直方图，个点
Dim PixelNumber As Integer
Width = UBound(SrcData,源码 2) + 1
Height = UBound(SrcData, 3) + 1
PixelNumber = Width * Height
For i = 0 To Width - 1
For j = 0 To Height - 1
Histgram(SrcData(0, i, j)) = Histgram(SrcData(0, i, j)) + 1 '统计图像的直方图
Next
Next
For i = 0 To
AllSum = AllSum + i * Histgram(i) ' 质量矩
AllPixelNumber = AllPixelNumber + Histgram(i) ' 质量
Next
MaxValue = -1#
For i = 0 To
PixelNumberSmall = PixelNumberSmall + Histgram(i)
PixelNumberBig = AllPixelNumber - PixelNumberSmall
If PixelNumberBig = 0 Then Exit For
SumSmall = SumSmall + i * Histgram(i)
SumBig = AllSum - SumSmall
ProbabilitySmall = CDbl(SumSmall) / PixelNumberSmall
ProbabilityBig = CDbl(SumBig) / PixelNumberBig
' Probability = PixelNumberSmall * PixelNumberBig * (ProbabilityBig - ProbabilitySmall) * (ProbabilityBig - ProbabilitySmall)
Probability = PixelNumberSmall * ProbabilitySmall * ProbabilitySmall + PixelNumberBig * ProbabilityBig * ProbabilityBig
If Probability > MaxValue Then
MaxValue = Probability
Threshold = i
End If
Next
For j = 0 To Width - 1
For k = 0 To Height - 1
If SrcData(0, j, k) <= Threshold Then
DestData(0, j, k) = 0
DestData(1, j, k) = 0
DestData(2, j, k) = 0
Else
DestData(0, j, k) =
DestData(1, j, k) =
DestData(2, j, k) =
End If
Next
Next
End Sub
'迭代法 (最佳阀值法)
'(1)求出图象的最大灰度值和最小灰度值，分别记为Zl和Zk，微信 公众 源码令初始阈值为：T=(Zl+Zk)/2
'(2)根据阈值TK将图象分割为前景和背景，分别求出两者的平均灰度值Z0和ZB:
'(3)令当前阈值Tk=(Z0+ZB)/2
'(4)若TK=TK+1， 则所得即为阈值，图书 源码否则转2，迭代计算。
Public Sub BestThresholdColorToBlackAndWhite(ByRef SrcData() As Byte, ByRef DestData() As Byte)
Dim i As Long, j As Long, k As Long
Dim red As Byte, green As Byte, blue As Byte
Dim Color As Long, newcolor As Long
Dim Width As Long, Height As Long
Dim PixelNumber As Integer
Dim Threshold As Integer, NewThreshold As Integer, MaxGrayValue As Integer
Dim MinGrayValue As Integer, MeanGrayValue1 As Integer, MeanGrayValue2 As Integer
Dim IP1 As Long, IP2 As Long, IS1 As Long, IS2 As Long
Dim Iteration As Long, Histgram() As Integer
Width = UBound(SrcData, 2) + 1
Height = UBound(SrcData, 3) + 1
PixelNumber = Width * Height
'求出图像中的最小和最大灰度值，并 计算阈值初值为
MaxGrayValue = 0: MinGrayValue =
For i = 0 To Width - 1
For j = 0 To Height - 1
Histgram(SrcData(0, i, j)) = Histgram(SrcData(0, i, j)) + 1 '统计图像的直方图
If MinGrayValue > SrcData(0, i, j) Then MinGrayValue = SrcData(0, i, j)
If MaxGrayValue < SrcData(0, i, j) Then MaxGrayValue = SrcData(0, i, j)
Next
Next
NewThreshold = (MinGrayValue + MaxGrayValue) / 2
While Threshold <> NewThreshold And Iteration <
Threshold = NewThreshold
'根据阈值将图像分割成目标和背景两部分，求出两部分的平均灰度值
For i = MinGrayValue To Threshold
IP1 = IP1 + Histgram(i) * i
IS1 = IS1 + Histgram(i)
Next
MeanGrayValue1 = CByte(IP1 / IS1)
For i = Threshold + 1 To MaxGrayValue
IP2 = IP2 + Histgram(i) * i
IS2 = IS2 + Histgram(i)
Next
MeanGrayValue2 = CByte(IP2 / IS2)
'求出新的阈值：
NewThreshold = (MinGrayValue + MaxGrayValue) / 2
Iteration = Iteration + 1
Wend
For j = 0 To Width - 1
For k = 0 To Height - 1
If SrcData(0, j, k) <= Threshold Then
DestData(0, j, k) = 0
DestData(1, j, k) = 0
DestData(2, j, k) = 0
Else
DestData(0, j, k) =
DestData(1, j, k) =
DestData(2, j, k) =
End If
Next
Next
End Sub
