Bersoft Image Measurement 9.0Measures an analyzes digital images.
Bersoft Image Measurement is intended for measuring and analyzing digital images. Measurements are done by pointing and clicking, using angle, distance, perimeter, area, point and line measurement tools or in an automated way, when calculating statistics and object finding. Supports image acquisition from TWAIN devices and many different types of images, including DICOM files. Now includes an image Database.
Bersoft Image Measurement 9.0 details
|Released:||Apr 6, 2018|
|File size:||9.67 MB|
|Keywords:||Image measurement, image analyzing, map measurement, medical image measurement, image analysis|
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Bersoft Image Measurement for Windows 10 - Full description
Bersoft Image Measurement (BIM) is designed as a flexible tool for acquiring, measuring and analyzing digital images. The measurements may be done by pointing and clicking or in an automated way, when doing statistical or analytical measurements. BIM can load many different types of images, including DICOM files, and also supports image acquisition from most TWAIN scanners. Angle, distance, perimeter, area, point and line measurements may be done using by using the tools in the Tools Palette. Spatial calibration is available to provide real world dimensional measurements such as kilometers, centimeters, millimeters, nanometers, microns, cm, miles, etc,. for both linear and The measurements are drawn over a measurement layer, so the original image is not altered in any way. Now includes an image Database. For convenient further statistical analysis the measurements can be exported as CVS, HTML, DOC or ASCII file formats. They also can be send directly to Excel or copied and pasted to any other program. Statistical measurement can be done either on a selected image area, the full image, or on several images at once. Count, mean, median, minimum, maximum, range, variance, standard deviation, standard error, coefficient of variation, skew, kurtosis and frequencies are supported. Images can be visualized and compared in different ways, using histograms (from images or selections), generating false color images, subtracting image backgrounds, merging images, adjusting brightness, gamma and contrast, inverting image colors, manipulating channels, applying spatial convolutions with user-defined convolution masks and morphing filters.