In this setting all pixel images are vectorized and embedded into the drawing as an entity Solid (filled rectangle). All solids that have close to the same color will be connected to create one common solid. This option is ideal for colorful pictures or bad quality scans.

This setting fills the small holes in the pixel traces.

This setting allows all holes in the pixel traces to be filled.

Often older scanned drawings will contain open pixel traces. This setting will prompt the program to close these open spaces. Under “For Experts Only” the user can select the distance between pixels.

Often older scanned drawings will have free pixels. Selecting this feature will ensure the removal of these unwanted pixels for a cleaner converted file.

 This setting will add a layer of pixels to the outer edge of the pixel trace.

This setting removes one layer of pixels from the outer edge of the pixel trace.

This setting assigns a separate color to entities from different layers. This way the user can better see the layer separation on the screen.

This program tries to find separate vector and hatch areas from in common pixel traces.

A good method to repair bad quality scanned images is to blur these images and then convert them into black/white images using the threshold. By blurring, the free pixels are removed, and the holes in the pixel traces are closed.

The program vectorizes all small pixel traces in lines using the “center line tracing” method.

The program vectorizes digital photos as color fillings in the form of an element Solid. Solids are very fast rectangle hatches used in CAD systems.

When selecting this option, all raster images are handled in their original resolution. For large raster images enabling this option may cause the resulting DWG / DXF file to contain millions of solid hatches.

When selecting this option, all pixel images are first scaled so that none of the dimensions are over the maximum values specified. The proportions of the image are not changed.

When selecting this option, the vectorized image is first converted into a black / white image and then vectorized. The threshold value for the color black is used.

When selecting this option, the contrasts in color will be increased and then the image will be vectorized. The threshold value for the color black and white is considered.

If this option is selected, all pixels which are brighter than the threshold of the color white in color images, and brighter than the threshold of the color black in b/w images, won‘t be converted.  This creates coherent hatching without any white spaces in between.

This program functions helps to find the contours in digital photos. Contours can be explained simply as a curved joining of all the continuous points (along the boundary), that have the same color or intensity. The contours are a useful tool for vectorization of digital photos.

This program offers five different contour finding methods.

This method was invented by John F. Canny a professor of computer science at the University of California, Berkeley. Canny‘s method is based on a gradient operator. The key idea here is to use two different thresholds to determine which point should belong to a contour.

 In Irwin Sobel‘s method we apply directional filters to detect edges in raster images to create contours for the vector image.

The method of Hanno Scharr is a modification of Sobel‘s method for edge detecting in raster images. This method is preferred when more accurate estimates of the gradient orientation is required.

The Laplace method is named after its founder Pierre-Simon De Laplace. The Laplace method uses the simplest elliptic operator to detect contours.

The method of cartoonization creates solid hatches out of digital images, which is reminiscent of the appearance of cartoons. These hatched areas are made from the DWG element Solid.