Perfect for the beginner, this demo illustrates simple object detection (segmentation, feature extraction), measurement, and filtering. Requires the Image Processing Toolbox (IPT) because it demonstrates some functions supplied by that toolbox, plus it uses the "coins" demo image supplied with that toolbox. If you have the IPT (you can check by typing ver on the command line), you should be able to run this demo code simply by copying and pasting this code into a new editor window, and then clicking the green "run" triangle on the toolbar.
First finds all the objects, then filters results to pick out objects of certain sizes. The basic concepts of thresholding, labeling, and regionprops are demonstrated with a simple example.
It's a good tutorial for those users new to MATLAB's image processing capabilities to learn on, before they go on to more sophisticated algorithms.
This Matlab code demonstrates an edge-based active contour model as an application of the Distance Regularized Level Set Evolution (DRLSE) formulation.
idTracker is a videotracking software that keeps the correct identity of each individual during the whole video. It works for many animal species including mice, insects (Drosophila, ants) and fish (zebrafish, medaka, stickleback). idTracker distinguishes animals even when humans cannot, such as for size-matched siblings, and reidentifies animals after they temporarily disappear from view or across different videos. It is robust, easy to use and general. Technique details and analyses of several applications are described in Pérez-Escudero et al (2014).
