Abstract: A system and method of classifying images of pathology. An image is received, normalized, and segmented normalizing the image; into a plurality of regions; A disease vector is automatically determining for the plurality of regions with at least one classifier comprising a neural network. Each of the respective plurality of regions is automatically annotated, based on the determined disease vectors. The received image is automatically graded based on at least the annotations. The neural network is trained based on at least an expert annotation of respective regions of images, according to at least one objective classification criterion. The images may be eye images, vascular images, or funduscopic images. The disease may be a vascular disease, vasculopathy, or diabetic retinopathy, for example.

Abstract: A system and method of classifying images of pathology. An image is received, normalized, and segmented normalizing the image; into a plurality of regions; A disease vector is automatically determining for the plurality of regions with at least one classifier comprising a neural network. Each of the respective plurality of regions is automatically annotated, based on the determined disease vectors. The received image is automatically graded based on at least the annotations. The neural network is trained based on at least an expert annotation of respective regions of images, according to at least one objective classification criterion. The images may be eye images, vascular images, or funduscopic images. The disease may be a vascular disease, vasculopathy, or diabetic retinopathy, for example.

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

Abstract: A system and method of classifying images of pathology. An image is received, normalized, and segmented normalizing the image; into a plurality of regions; A disease vector is automatically determining for the plurality of regions with at least one classifier comprising a neural network. Each of the respective plurality of regions is automatically annotated, based on the determined disease vectors. The received image is automatically graded based on at least the annotations. The neural network is trained based on at least an expert annotation of respective regions of images, according to at least one objective classification criterion. The images may be eye images, vascular images, or funduscopic images. The disease may be a vascular disease, vasculopathy, or diabetic retinopathy, for example.

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

Abstract: A method for encoding an image descriptor (H) based on gradient histograms (hp) into a transformed descriptor (V) having transformed subdescriptors (vp), wherein each gradient histogram (hp) includes a plurality of histogram bins (hi) and each subdescriptor (vp) includes a set of values (vj), wherein the subdescriptors (vp) are generated according to an element utilization order list specifying a subdescriptor index (p) of the set of sub descriptors (vp) and an element index (j) of the set of values (vj).

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

Abstract: A method for encoding an image descriptor (H) based on gradient histograms (hp) into a transformed descriptor (V) having transformed subdescriptors (vp), wherein each gradient histogram (hp) includes a plurality of histogram bins (hi) and each subdescriptor (vp) includes a set of values (vj), wherein the subdescriptors (vp) are generated according to an element utilisation order list specifying a subdescriptor index (p) of the set of sub descriptors (vp) and an element index (j) of the set of values (vj).

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

Abstract: A method and apparatus for coding and decoding the fingerprint of a multimedia item such as video or audio is disclosed. A multimedia content temporal, such as a video segment or audio segment, is described by a coarse fingerprint and a plurality of fine fingerprints, each fine fingerprint corresponding to a temporal sub-interval of said temporal interval, said temporal sub-interval typically being smaller than said temporal interval. One or more fine fingerprints are encoded in a non-predictive way, with no reference to the temporally neighboring signatures, and one or more fine fingerprints are encoded in a predictive way, from the temporally neighboring signatures.

Abstract: A method and apparatus for processing a first sequence of images and a second sequence of images to compare the first and second sequences is disclosed. Each of a plurality of the images in the first sequence and each of a plurality of the images in the second sequence is processed by (i) processing the image data for each of a plurality of pixel neighborhoods in the image to generate at least one respective descriptor element for each of the pixel neighborhoods, each descriptor element comprising one or more bits; and (ii) forming a plurality of words from the descriptor elements of the image such that each word comprises a unique combination of descriptor element bits. The words for the second sequence are generated from the same respective combinations of descriptor element bits as the words for the first sequence.

Abstract: A method of representing at least one image comprises deriving at least one descriptor based on color information and color interrelation information for at least one region of the image, the descriptor having at least one descriptor element, derived using values of pixels in said region, wherein at least one descriptor element for a region is derived using a non-wavelet transform. The representations may be used for image comparisons.

Abstract: A method of representing and analysing images comprises producing a plurality of descriptors of an image at one or more scales and for one or more color channels, said descriptors capturing color content and interrelation information within the regions, and associating the descriptors in a plurality of ways based on their characteristics such as scale, color channel, feature semantics, and region, and comparing such representations of images to assess the similarity of images.

Abstract: A method of representing at least one image comprises deriving at least one descriptor based on color information and color interrelation information for at least one region of the image, the descriptor having at least one descriptor element, derived using values of pixels in said region, wherein at least one descriptor element for a region is derived using a non-wavelet transform. The representations may be used for image comparisons.

Abstract: A method and apparatus for coding and decoding the fingerprint of a multimedia item such as video or audio is disclosed. A multimedia content temporal, such as a video segment or audio segment, is described by a coarse fingerprint and a plurality of fine fingerprints, each fine fingerprint corresponding to a temporal sub-interval of said temporal interval, said temporal sub-interval typically being smaller than said temporal interval. One or more fine fingerprints are encoded in a non-predictive way, with no reference to the temporally neighbouring signatures, and one or more fine fingerprints are encoded in a predictive way, from the temporally neighbouring signatures.

Abstract: A method of representing at least one image comprises deriving at least one descriptor based on colour information and colour interrelation information for at least one region of the image, the descriptor having at least one descriptor element, derived using values of pixels in said region, wherein at least one descriptor element for a region is derived using a non-wavelet transform. The representations may be used for image comparisons.

Abstract: A method of representing and analysing images comprises producing a plurality of descriptors of an image at one or more scales and for one or more colour channels, said descriptors capturing colour content and interrelation information within the regions, and associating the descriptors in a plurality of ways based on their characteristics such as scale, colour channel, feature semantics, and region, and comparing such representations of images to assess the similarity of images.

Abstract: A technique is disclosed for detecting gradual transitions between frames of a video sequence such as fade and dissolve transitions. For each frame, the intensity values of pixels at corresponding positions within a window of frames including the subject frame are compared, and signs are allocated to the calculated differences. The number of each type of sign is determined for each pixel position and the larger number of matching signs is assigned as a measure of the monotonicity of the direction of intensity variations at the pixel position between the frame and the surrounding frames. A global monotonicity measure is then calculated for the frame as a whole using the monotonicity values for each pixel position. This is repeated for each frame to generate a temporal sequence of frame intensity change monotonicity measures. Slopes within this temporal sequence representative of gradual Transitions between video frames are detected.

Abstract: A method of representing at least one image comprises deriving at least one descriptor based on color information and color interrelation information for at least one region of the image, the descriptor having at least one descriptor element, derived using values of pixels in said region, wherein at least one descriptor element for a region is derived using a non-wavelet transform. The representations may be used for image comparisons.

Abstract: A method of representing and analyzing images comprises producing a plurality of descriptors of an image at one or more scales and for one ore more color channels, said descriptors capturing color content and interrelation information within the regions, and associating the descriptors in a plurality of ways based on their characteristics such as scale, color channel, feature semantics, and region, and comparing such representations of images to assess the similarity of images.