Abstract: Disclosed herein is a method for authenticating a user identity according to predetermined user interactions, including the use of at least one hardware processor for obtaining at least one image from a database, presenting said at least one image to a user through an authentication interface, requesting from the user at least one user interaction related to said at least one image, obtaining an input comprising at least one user interaction input, comparing said at least one user interaction input with said at least one user interaction to validate the user identity and to validate the user is a human, providing an indication regarding the user identity according to a result of comparing said at least one user interaction input with said at least one user interaction.

Abstract: Disclosed herein is a method for authenticating a user identity according to predetermined user interactions, including the use of at least one hardware processor for obtaining at least one image from a database, presenting said at least one image to a user through an authentication interface, requesting from the user at least one user interaction related to said at least one image, obtaining an input comprising at least one user interaction input, comparing said at least one user interaction input with said at least one user interaction to validate the user identity and to validate the user is a human, providing an indication regarding the user identity according to a result of comparing said at least one user interaction input with said at least one user interaction.

Abstract: Digitized image data are input into a processor where a detection component identifies the areas (objects) of particular interest in the image and, by segmentation, separates those objects from the background. A feature extraction component formulates numerical values relevant to the classification task from the segmented objects. Results of the preceding analysis steps are input into a trained learning machine classifier which produces an output which may consist of an index discriminating between two possible diagnoses, or some other output in the desired output format. In one embodiment, digitized image data are input into a plurality of subsystems, each subsystem having one or more support vector machines. Pre-processing may include the use of known transformations which facilitate extraction of the useful data. Each subsystem analyzes the data relevant to a different feature or characteristic found within the image.