Abstract: A method of generating a descriptor of at least part of an image includes receiving image data representing the at least part of the image. The image data is processed to identify at least one texture characteristic of the at least part of the image, thereby generating texture data indicative of a texture of the at least part of the image. The texture data is processed with the image data, thereby generating weighted texture data. A descriptor of the at least part of the image is generated using the weighted texture data.

Abstract: The present application relates to a method of generating a keypoint descriptor for identifying an object in an image or a sequence of images, the keypoint descriptor being substantially invariant to a transformation of the object in the image. The present application further relates to a method of identifying an object in an image using a keypoint descriptor; and processing apparatus and computer program products for implementing a method of the present application.

Abstract: Disclosed embodiments relate to a systems and methods of identifying a target object in an image using image processing. Template data is stored which represents a template orientation field indicative of an orientation of each of a plurality of features of a template object. Image data may be received and processed to generate an image orientation field indicating an orientation corresponding to the plurality of image features. The image data may be further processed to generate image confidence data based on at least one characteristic for use in identifying the target object in a given image, and the characteristic may be indicative of an increased likelihood that at least one part of the given image represents at least part of the target object, relative to other parts of the given image.

Abstract: A method of generating a descriptor of at least part of an image includes receiving image data representing the at least part of the image. The image data is processed to identify at least one texture characteristic of the at least part of the image, thereby generating texture data indicative of a texture of the at least part of the image. The texture data is processed with the image data, thereby generating weighted texture data. A descriptor of the at least part of the image is generated using the weighted texture data.

Abstract: The present application relates to a method of generating a keypoint descriptor for identifying an object in an image or a sequence of images, the keypoint descriptor being substantially invariant to a transformation of the object in the image. The present application further relates to a method of identifying an object in an image using a keypoint descriptor; and processing apparatus and computer program products for implementing a method of the present application.

Abstract: The present application relates to a method of generating a keypoint descriptor for identifying an object in an image or a sequence of images, the keypoint descriptor being substantially invariant to a transformation of the object in the image.

Abstract: Among other things, a method is disclosed comprising: receiving image data representing an image; processing the data to generate orientation information; processing the data using the orientation information to measure a quantity called local phase in a direction perpendicular to the orientation of a putative vessel; using the phase measurements from three collinear image locations or from two locations to detect the centerline of a symmetric image structure, such as a blood vessel, and to locate a center-point defined by the intersection of the centerline with the line created by the measurement locations.

Abstract: Disclosed embodiments relate to a systems and methods of identifying a target object in an image using image processing. Template data is stored which represents a template orientation field indicative of an orientation of each of a plurality of features of a template object. Image data may be received and processed to generate an image orientation field indicating an orientation corresponding to the plurality of image features. The image data may be further processed to generate image confidence data based on at least one characteristic for use in identifying the target object in a given image, and the characteristic may be indicative of an increased likelihood that at least one part of the given image represents at least part of the target object, relative to other parts of the given image.

Abstract: The present application relates to a method of generating a keypoint descriptor for identifying an object in an image or a sequence of images, the keypoint descriptor being substantially invariant to a transformation of the object in the image.

Abstract: The present invention relates to a method of identifying a target object in an image using image processing. It further relates to apparatus and computer software implementing the method. The method includes storing template data representing a template orientation field indicative of an orientation of each of a plurality of features of a template object; receiving image data representing the image; processing the image data to generate an image orientation field indicating an orientation corresponding to the plurality of image features; processing the image orientation field using the template orientation field to generate a match metric indicative of an extent of matching between at least part of the template orientation field and at least part of the image orientation field; and using the match metric to determine whether or not the target object has been identified in the image. Image and/or template confidence data is used to generate the match metric.

Abstract: The present invention relates to a method of generating a keypoint descriptor for identifying an object in an image or in a sequence of images, the keypoint descriptor being substantially invariant to a transformation of the object in the image.

Abstract: The present invention relates to a method of generating a keypoint descriptor for identifying an object in an image or in a sequence of images, the keypoint descriptor being substantially invariant to a transformation of the object in the image.

Abstract: Among other things, a method is disclosed comprising: receiving image data representing an image; processing the data to generate orientation information; processing the data using the orientation information to measure a quantity called local phase in a direction perpendicular to the orientation of a putative vessel; using the phase measurements from three collinear image locations or from two locations to detect the centerline of a symmetric image structure, such as a blood vessel, and to locate a center-point defined by the intersection of the centerline with the line created by the measurement locations.

Abstract: The present invention relates to a method of identifying a target object in an image using image processing. It further relates to apparatus and computer software implementing the method. The method includes storing template data representing a template orientation field indicative of an orientation of each of a plurality of features of a template object; receiving image data representing the image; processing the image data to generate an image orientation field indicating an orientation corresponding to the plurality of image features; processing the image orientation field using the template orientation field to generate a match metric indicative of an extent of matching between at least part of the template orientation field and at least part of the image orientation field; and using the match metric to determine whether or not the target object has been identified in the image. Image and/or template confidence data is used to generate the match metric.