Image Data

Formats:

• .BMP Windows Bitmap
• .DWF Autocad drawing file.
• .GIF files are the defacto standard for raster image graphics on the World Wide Web. see also: services
• .JPEG An image compression format ideal to greyscale and color photograps
• .PCL Printer Control Language.
• .PCX Older format graphic files
• .PDF Portable Document Format. From Adobe Systems Corp^
• .WMF Windows Meta File. see also: Caolán McNamara's Guide for non-windows programmers
• .XBM

Geocoding Images

Video IO

Image Recognition Methods

Graphics

also:

• Visual Filters in Internet Explorer
• The Scientist and Engineer's Guide to Digital Signal Processing:
  • Special Processing Techniques
  • Moving Average Filters
  • Recursive Filters
  • Custom Filters
• October 2003 MassMind Newsletter: Ranging via Camera and Laser
• Cameras

See also:

• https://www.youtube.com/watch?v=C_zFhWdM4ic How filters work, with box blur and Gaussian blur as examples.
  
  Box Blur is done by a Normal Unity Kernel Convolution. Unity meaning that every element of the kernels matrix is 1. Normal meaning the pixels are then averaged by dividing each by the absolute sum of all the pixels in the matrix.
  
  Gaussian Blur uses a matrix where the edge values are 1, but the values closer to the center follow a Normal distribution. A simple example might be: Gaussian
  Kernel
  1 2 1
  2 4 2
  1 2 1

  
  

• https://www.youtube.com/watch?v=uihBwtPIBxM How the Sobel edge detection filter works. Including finding the angle of the edge.+ This provides both the edge, and the angle of the edge. It uses Kernel Convolution with two matrixs, one applied to find horizontal edge, and another for vertical.
  Vertical
  (Y) Kernel
  -1 -2 -1
  0 0 0
  1 2 1
  Horizontal
  (X) Kernel
  -1 0 1
  -2 0 2
  -1 0 1

  These are then combined into a single result by squaring the value of each pixel from the X result, adding that to the square of the corrisponding pixel in the Y result, and then taking the square root of that. We can also take each Y pixel and divide it by the X pixel then take the arc tangent of that to find the angle of the edge at that point.
  

• https://www.youtube.com/watch?v=sRFM5IEqR2w The Canny edge detection filter adds on to Sobel by thinning all the edges to 1 pixel by looking for local maximum pixels along the direction of the edge. It then removes weak edges via hysteresis thresholding. Two thresholds are set, and edges above the top one are kept, edges blow the bottom are removed, and edges between are kept if they are next to a kept edge.
  
• http://www.bitquill.net/trac/wiki/Android/OCR (see the blog post) Given a greyscale image of dimisions m x n, the lighting will often change from one part of the image to another. To pick out details consistantly, you need to set the threshold individually for each pixel (i,j) as the mean intensity of pixels in a w x w neighborhood around the pixel. On each row, you might do
  for i = 0 to N-1: s = 0; for k = max(i-r,0) to min(i+r,N-1): s += a[k];
  where w=2r+1. (r is half the width of the window). But it turns out that this is faster:
  Initialize s = sum(a[0]..a[r]); for i = 1 to N-1: if i > r: s -= a[i-r-1]; if i < N-r: s += a[i+r]
  at the end of each, s is the threshold for pixel a[i].

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