CVB Manto is a versatile software that is able to solve optical recognition
tasks not previously possible. The software is based on a specially
adapted technology based on support vector machines.
CVB Manto uses all image information from multiple image planes and
as such can be applied to monochrome, colour and even multi-spectral
images. It automatically identifies the key features that help to identify
the object’s class. Once properly trained it can also identify product
characteristics that would be very difficult using other techniques, such
as different paper types or the ripeness of fruit.
Food and packaging industry
To create reliable inspection solutions that can deal with the changing organic nature of products
For most difficult applications such as reading stamped or punched numbers on metal or cast surfaces with different degrees of readability and depth
The analysis of the surface structure (for example recognition of different kinds of wood, classification of herbs and spices or inspection of quality of meat)
Identification of vehicles by their class, brand or model or for number plate reading
Complex OCR tasks like handwriting
Ideal for recognising and classifying organically varying features, i.e. fruits, vegetables, plants
Cannot be over trained – the more examples you give, the better the recognition
Linear interpolation mode – ideal for dynamic grading with an interpolation of the grade between two fixed grades
Special texture mode for identification of textures and organic patterns
Finlays wanted to count flower heads with machine vision. Learn how the system was developed with our software CVB Manto and what the results look like.
The programming library Common Vision Blox ist used to check barcode, expiration date as well as the fruittype.
The versatile software CVB Manto checks whether the contents of the package of spices matches to the label of the package. CVB Manto is the ideal tool for recognising and classifying organically varying features.
CVB Manto is the ideal tool for reliable inspection of organic products like cookies. Compared to other more academic implementations of SVM the user of CVB Manto does not need to select the relevant features in an image to create a robust object differentiation.
This video shows in an easy to follow step by step explanation how to acquire
and display an image with the STEMMER IMAGING machine vision software Common
Vision Blox (CVB). This tutorial is mainly intended for beginners in CVB