Page 105 - Klic-N-Kut User Manual

6. Tracing

6.01 Raster versus Vector

 All graphics are either raster or vector and there is no third type. While you can often tell by the file format,
even that isn’t always a good way to know for certain. For example, a PDF file can be made from either
raster images or vector images and some PDF’s will contain both types.
 You may not be able to tell, at first glance, whether an image is a raster or a vector. For example, this
screen shot shows the same image in both formats:

Raster Vector
 Most everyone today has a digital camera and, at the very least, has heard the term “mega-pixel.” A pixel is
a square that is black, white, or colored. Photographs are made up of millions of these pixels to create the
image you see. If you zoom in close enough on any raster image, you can see these tiny pixels. But when
you zoom in close on the same area in the vector version, you will instead see lines and curves, not
squares/pixels:

Raster Vector

 A vector image isn’t made up of pixels. Instead, a vector is like a connect-the-dot puzzle in which little dots
(called nodes or points) are connected to each another with paths (either straight lines or curves). Digital die
cutters need those paths so that that they can communicate to the cutter where the blade should travel in
order to make the cuts you want… kind of like a road map. In MTC, the nodes look like this:

 As mentioned earlier, you can often tell whether a file is a raster or a vector based on the file format. Here
are some guidelines:

Raster: BMP, JPG, TIF, PNG, GIF Vector: AI, EPS, WMF, DXF, SVG Either: PDF, sometimes EPS & WMF

 To convert a raster into a vector, MTC offers two options: Pixel Trace and Manual Trace. Because the
Pixel Trace feature in MTC is so fast and powerful, it is always worth trying it first. The only situation in
which it may not be able to provide the results you need are (1) the image is very tiny or has a very poor
resolution or (2) the image has poor contrast between one part and the next. For example, imagine a brown
dog lying on brown carpet. How would the software know what part is the dog and what part is the carpet?
Thus you may need to manually trace some images, so both functions are covered, in detail, in this chapter.

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