There is provided a computerized method and system of controlling a quality measure in a compression quality evaluation system, the method comprising: calculating a grain value indicative of an extent of grain present in an input image, the grain value being calculated based on one or more features characterizing a base image related to the input image; and configuring the quality measure upon a criterion being met by the value, the quality measure being indicative of perceptual quality of a compressed image compressed from the input image. The calculated grain value may be dependent also on further characteristics of the input image, or in the case of a sequence of images, dependent also on the relation between the image and the preceding image.

There is provided a computerized method and system of controlling a quality measure in a compression quality evaluation system, the method comprising: calculating a grain value indicative of an extent of grain present in an input image, the grain value being calculated based on one or more features characterizing a base image related to the input image; and configuring the quality measure upon a criterion being met by the value, the quality measure being indicative of perceptual quality of a compressed image compressed from the input image. The calculated grain value may be dependent also on further characteristics of the input image, or in the case of a sequence of images, dependent also on the relation between the image and the preceding image.

Systems and methods suitable for capable of autonomous crack detection in surfaces by analyzing video of the surface. The systems and methods include the capability to produce a video of the surfaces, the capability to analyze individual frames of the video to obtain surface texture feature data for areas of the surfaces depicted in each of the individual frames, the capability to analyze the surface texture feature data to detect surface texture features in the areas of the surfaces depicted in each of the individual frames, the capability of tracking the motion of the detected surface texture features in the individual frames to produce tracking data, and the capability of using the tracking data to filter non-crack surface texture features from the detected surface texture features in the individual frames.

For generating a breathing alert is disclosed, a method receives a video stream of a subject. The method further estimates a breathing signal from the video stream. The method determines one of a large-scale motion and/or a breathing event of the subject based on the breathing signal. The method generates an alert if both no breathing event is identified and no large-scale motion of the subject is identified within an event time interval.

For generating a breathing alert is disclosed, a method receives a video stream of a subject. The method further estimates a breathing signal from the video stream. The method determines one of a large-scale motion and/or a breathing event of the subject based on the breathing signal. The method generates an alert if both no breathing event is identified and no large-scale motion of the subject is identified within an event time interval.

A medical scan triaging system is operable to train a computer vision model and to generate abnormality data indicating abnormality probabilities for medical scans via the computer vision model. A first subset of medical scans is determined by identifying medical scans with abnormality probabilities greater than a first probability value of a triage probability threshold. A second subset of medical scans is determined by identifying medical scans with abnormality probabilities less than the first probability value. An updated first subset of medical scans is determined by identifying medical scans with abnormality probabilities greater than a second probability value of an updated triage probability threshold. An updated second subset of the plurality of medical scans is determined by identifying medical scans with a abnormality probabilities less than the second probability value. The updated first subset of medical scans is transmitted to client devices.

A medical scan triaging system is operable to train a computer vision model and to generate abnormality data indicating abnormality probabilities for medical scans via the computer vision model. A first subset of medical scans is determined by identifying medical scans with abnormality probabilities greater than a first probability value of a triage probability threshold. A second subset of medical scans is determined by identifying medical scans with abnormality probabilities less than the first probability value. An updated first subset of medical scans is determined by identifying medical scans with abnormality probabilities greater than a second probability value of an updated triage probability threshold. An updated second subset of the plurality of medical scans is determined by identifying medical scans with a abnormality probabilities less than the second probability value. The updated first subset of medical scans is transmitted to client devices.

A method for transforming an image descriptor, based on a gradient histogram (h) having a plurality of histogram bins (h.sub.i), into a transformed gradient histogram descriptor (v) including a set of values (v.sub.j), wherein it is provided the step of applying at least one criterium for calculating the set of values (v.sub.j), at least one criterium having a location criterium of the histogram bins (h.sub.i). The invention also relates to an image processing device suitable for carrying out the method.

System and method for detecting the authenticity of products by detecting a unique chaotic signature. Photos of the products are taken at the plant and stored in a database/server. The server processes the images to detect for each authentic product a unique authentic signature which is the result of a manufacturing process, a process of nature etc. To detect whether the product is genuine or not at the store, the user/buyer may take a picture of the product and send it to the server (e.g. using an app installed on a portable device or the like). Upon receipt of the photo, the server may process the receive image in search for a pre-detected and/or pre-stored chaotic signature associated with an authentic product. The server may return a response to the user indicating the result of the search. A feedback mechanism may be included to guide the user to take a picture at a specific location of the product where the chaotic signature may exist.

System and method for detecting the authenticity of products by detecting a unique chaotic signature. Photos of the products are taken at the plant and stored in a database/server. The server processes the images to detect for each authentic product a unique authentic signature which is the result of a manufacturing process, a process of nature etc. To detect whether the product is genuine or not at the store, the user/buyer may take a picture of the product and send it to the server (e.g. using an app installed on a portable device or the like). Upon receipt of the photo, the server may process the receive image in search for a pre-detected and/or pre-stored chaotic signature associated with an authentic product. The server may return a response to the user indicating the result of the search. A feedback mechanism may be included to guide the user to take a picture at a specific location of the product where the chaotic signature may exist.