Getting started with the Scilab Computer Vision Module
Scilab Computer Vision Module (sciCV) is the Scilab interface to the OpenCV library (in version 2.4.13).
The purpose of this toolbox is to provide an access to all the functions and objects of OpenCV in Scilab.
The following feature domains are (or will be) covered:
highgui)imgproc)objdetect)feature2d)video)photo)calib3d)flann)stitching)videostab)superres)ml)gpu)About video, the toolbox supports video reading/writing as it includes the FFmpeg component (in its LGPL version), with the h264 openh264 open source codec.
The interface is the same (as much as possible) as the OpenCV API version 2, same function names and parameters, but adapted to Scilab. For example pointers are masked or their usage is avoided as much as possible. Argument passing is simplified, as Scilab support multi output argument.
This interface is also designed to combine performance and convenience. Conversion to output Scilab objects is done only when it is necessary (i.e. without sacryfing performance). For example an image read is not automatically converted to a Scilab matrix, but only when image data must be extracted, and further manipulated in Scilab. Unconverted OpenCV objects can be manipulated as Scilab matrixes, to this end, standard operators (extraction, ...) are redefined. On the other hand, conversion from Scilab objects to OpenCV objects (in input) is done automatically.
Installation is also simplified. No installation of OpenCV, or system configuration, are needed to use sciCV. The toolbox embeds (and loads) automatically all the necessary OpenCV binaries (whatever platform is).
Once the toolbox loaded in Scilab, the only needed operation is to initialize the module with scicv_Init().
The following platforms are supported: