|Excel Thermo Import|
|Excel Unit Operation|
|Matlab Unit Operation|
|Matlab Thermo Import|
|OO Calc Thermo Import|
|SciLab Unit Operation|
|SciLab Thermo Import|
|Python Thermo Import|
Your image may be noisy, or the amount of colors in your image may not match the content. You may want to use one of the filters below to fix this:
Use the contrast and brightness filter to adjust your image after it comes from the scanner. You can adjust contrast and brightness while previewing the image.
The remove noise filter will make all colors that are similar to the background color equal to the background color. After that, it will find individual pixels that are not equal to the background color, and remove them.
You can adjust the threshold for deciding whether a pixel is equal to the background color while previewing the image.
The black and white filter is useful when you have a graph that is in two colors, and the image was scanned in gray-scales or color mode. The filter lets you adjust the threshold for black or white while previewing the image.
The flatten filter reduces the resolution per color. This is useful for images that have been scanned in gray-scale or color mode, in which only a few shades of each color are present. This filter will make those color shades equal. For gray-scale images you may want to convert to gray-scale first, if your image has been scanned in color.
You can adjust the color resolution while previewing the image.
The gray-scale filter removes color information. This is useful for gray-scale or uniformly colored graphs that have been scanned in color mode.
The invert color filter inverts all colors in the image. This is useful if your image has been taken from a source with a black background color.
The edge filter highlights regions of high contrast. The effect of this is that regions on which color changes will become dark, whereas constantly colored regions are white. This filter is useful for tracking the boundaries of colored regions in graphs.