Abstract: A method, system and computer programs for traceability of living specimens are provided.

Abstract: A method and a device for the characterization of living specimens from a distance are disclosed. The method comprises: acquiring an image of a living specimen and segmenting the image, providing a segmented image; measuring a distance to several parts of said image, providing several distance measurements, and selecting a subset of those contained in the segmented image. The method also processes the segmented image and the distance measurements referred to different positions contained within the segmented image by characterizing the shape and the depth of the living specimen and by comparing a shape analysis map and a depth profile analysis map. If a result of the comparison is comprised inside a given range, parameters of the living specimen are further determined including posture parameters, location or correction of anatomical reference points and/or body size parameters, and/or a body map of the living specimen is represented.

Abstract: A method and system of non-invasively marking and discrimination of livestock are disclosed. The method comprises receiving, by a computing system, information related to a livestock animal and determining at least one feature of the livestock animal using the received information; and marking, by a light-based marking device operatively connected to the computing system, the livestock animal by projecting an identifier related to the determined feature, on a part of or in an area nearby the livestock animal, or in at least one screen, wherein said marking is performed from a given distance from the livestock animal, said given distance being comprised within a given marking range.

Abstract: A method and a device for the characterization of living specimens from a distance are disclosed. The method comprises: acquiring an image of a living specimen and segmenting the image, providing a segmented image; measuring a distance to several parts of said image, providing several distance measurements, and selecting a subset of those contained in the segmented image. The method also processes the segmented image and the distance measurements referred to different positions contained within the segmented image by characterizing the shape and the depth of the living specimen and by comparing a shape analysis map and a depth profile analysis map. If a result of the comparison is comprised inside a given range, parameters of the living specimen are further determined including posture parameters, location or correction of anatomical reference points and/or body size parameters, and/or a body map of the living specimen is represented.

Abstract: The method comprising: acquiring, by a two-dimensional camera (7), in a scene, a two dimensional image of at least one object (200); identifying the object (200) within the acquired two dimensional image; calculating, by a first means, the size of a pixel of the object (200) in the acquired and segmented two dimensional image taking into account the distance between the object (200) and the two-dimensional camera (7); and calculating, by a second means, several parameters including at least the size, dimensions, body part dimensions, body features, weight and/or volume of the object (200) by using said calculated size of the pixel and an a priori model of the object (200), wherein said a priori model includes information linking different parts, contours or shapes representative of several objects (200), previously acquired with a two-dimensional camera, with several parameters said several objects (200).

Abstract: The method comprising: acquiring, by a two-dimensional camera (7), in a scene, a two dimensional image of at least one object (200); identifying the object (200) within the acquired two dimensional image; calculating, by a first means, the size of a pixel of the object (200) in the acquired and segmented two dimensional image taking into account the distance between the object (200) and the two-dimensional camera (7); and calculating, by a second means, several parameters including at least the size, dimensions, body part dimensions, body features, weight and/or volume of the object (200) by using said calculated size of the pixel and an a priori model of the object (200), wherein said a priori model includes information linking different parts, contours or shapes representative of several objects (200), previously acquired with a two-dimensional camera, with several parameters said several objects (200).

Abstract: The method comprising acquiring and analyzing by computer means image information of video sequences of two or more dimensions obtained from contrast-enhanced signals, for example ultrasound, coherence tomography, fluorescence images, or Magnetic Resonance Imaging, of a body part or tissue, for example of an organ, of a living subject; detecting events from said information of video sequences; selecting a Region of Interest of said body part or tissue; computing a first graph representative of a local vascular network of said image information of video sequences in which the edges of the graph are estimated by the temporal relationship among spatially remote signals of said image information of video sequences within a set of video sequences; and using said graph for assessment of vascular networks.

Abstract: The method comprising acquiring and analysing by computer means image information of video sequences of two or more dimensions obtained from contrast-enhanced signals, for example ultrasound, coherence tomography, fluorescence images, or Magnetic Resonance Imaging, of a body part or tissue, for example of an organ, of a living subject; detecting events from said information of video sequences; selecting a Region of Interest of said body part or tissue; computing a first graph representative of a local vascular network of said image information of video sequences in which the edges of the graph are estimated by the temporal relationship among spatially remote signals of said image information of video sequences within a set of video sequences; and using said graph for assessment of vascular networks.

Abstract: Equipment for infrared vision of anatomical structures applicable to assist the physicians in endoscopic, fetoscopic or laparoscopic operations and methods for signal processing to enhance said vision, comprising two units that work together: a multimodal or multispectral imaging unit, constituted by a device comprising an endoscope or fetoscope or laparoscope, and additional optical systems to acquire multimodal images of the interior of the patient's body; and an image processing unit, to which said images are transferred, comprising processing devices with a navigation interface which process said images and display the patient's enhanced anatomical map image and the endoscope location, equipped with hardware and software that apply at least five different vision-enhancing methods, namely normalization, segmentation, tracking, mapping and fusion.