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Tech Explained: Autotracing


The difference between bit-mapped and vector images, and how autotrace converts them

In design, there are two types of images – bitmap (or raster) and vector. Bitmap images are made up of tiny, coloured dots called pixels. Vector images, in contrast, are created by using mathematical formulas as instructions to draw lines and curves. These create the outlines of shapes, which can be combined and filled to create an image. Autotracing is used to convert bitmap images into vector. It is a useful technique not only for professional designers, but for anyone interested in image design. So, how does autotracing work, and why is it so useful?

The first question to answer: why is it necessary to convert a bitmap image into a vector image? Bitmap images store information about the colour of each pixel, while vector images only need to store the mathematical formulas that make up the image. This means that vector images are smaller and require less memory. They are also more scalable than bitmap images. When bitmap images are blown up, the individual pixels become larger, which creates jagged or blurred edges. When a vector image is scaled up, the image is redrawn using the mathematical formula, leaving an image that looks just like the original, only larger.

Here is where autotracing comes in handy. To convert from bitmap to vector, designers need to “trace over” the original bitmap image with new vector lines. This can be done manually or by using an automatic tracing (autotrace) program. When tracing manually, a mouse or graphics “pen” is used to trace over every line. This is time consuming and requires a degree of artistic sensibility and skill. Automatic tracing saves time by using software to detect the lines and edges of the bitmap image, and then redraws them as vector images. Autotracing is fast, but works best with images that are high-quality to begin with, and that have simple shapes and limited shading. Manual tracing is less accurate than autotracing, but works with images of any quality.

Autotracing is also particularly useful for people working on tight deadlines, or working with scanned images, or images composed largely of flat shapes and lines such as architectural and engineering drawings. Those working with photos or poor-quality images may be better off manually tracing them.

A number of recent innovations have created ways for shoppers to customise or design their own products. For example, apps now allow users to design their own boardshorts, bridesmaid dresses and computer games. Anyone using these innovations — and who has little or no design experience — may find autotracing helpful in converting photos or ideas into unique items.