Stmicroelectronics S.r.l.

Alessandro Capra

Alfio Castorina

Nunziata Ivana Guarneri

Arcangelo Ranieri Bruna

Giuseppe Spampinato

Massimo Mancuso

Francesco Pappalardo

Sebastiano Battiato

Mirko Guarnera

Giuseppe Messina

Marco Farina

Paolo Antonino Foderá

Filippo Naccari

Elena Salurso

Raimondo Schettini

Giovanni Gallo

Francesca Gasparini

Giovanni Maria Farinella

Francesco Maria Virlinzi

Silvia Corchs

Hervé Broquin

Francesco Cristaldi

Silvia Maria Francesca Cariolo

Paolo Antonino Foderà

Hand gestures, such as hand or finger hovering, in the proximity space of a sensing panel are detected from X-node and Y-node sensing signals indicative of the presence of a hand feature at corresponding row and column locations of a sensing panel. Hovering is detected by detecting the locations of maxima for a plurality of frames over a time window for sets of X-node and Y-node sensing signals by recognizing a hovering gesture if the locations of the maxima detected vary over the plurality of frames for one of the sets of sensing signals and not for the other of set. Finger shapes are distinguished over 'ghosts' generated by palm or fist features by transforming the node-intensity representation for the sensing signals into a node-distance representation based on distances of detection intensities for a number of nodes under a peak for a mean point between valleys adjacent to the peak.

Gesture recognition method, apparatus and device, computer program product therefor

In an embodiment, hand gestures, such as hand or finger hovering, in the proximity space of a sensing panel are detected from X-node and Y-node sensing signals indicative of the presence of a hand feature at corresponding row locations and column locations of a sensing panel. Hovering is detected by detecting the locations of maxima for a plurality of frames over a time window for a set of X-node sensing signals and for a set of Y-node sensing signals by recognizing a hovering gesture if the locations of the maxima detected vary over the plurality of frames for one of the sets of X-node and Y-node sensing signals while remaining stationary for the other of the sets of X-node and Y-node sensing signals. Finger shapes are distinguished over 'ghosts' generated by palm or first features by transforming the node-intensity representation for the sensing signals into a node-distance representation, based on the distances of the detection intensities for a number of nodes under a peak for a mean point between the valleys adjacent to the peak.

In an embodiment, hand gestures, such as hand or finger hovering, in the proximity space of a sensing panel are detected from X-node and Y-node sensing signals indicative of the presence of a hand feature at corresponding row locations and column locations of a sensing panel. Hovering is detected by detecting the locations of maxima for a plurality of frames over a time window for a set of X-node sensing signals and for a set of Y-node sensing signals by recognizing a hovering gesture if the locations of the maxima detected vary over the plurality of frames for one of the sets of X-node and Y-node sensing signals while remaining stationary for the other of the sets of X-node and Y-node sensing signals(Y). Finger shapes are distinguished over 'ghosts' generated by palm or fist features by transforming the node-intensity representation for the sensing signals into a node-distance representation, based on the distances of the detection intensities for a number of nodes under a peak for a mean point between the valleys adjacent to the peak.

An embodiment of a method for processing finger-detection data produced by a touch screen includes: computing the area of the finger-data map and extracting the main axes from the finger-data map, computing the lengths and orientations of the main axes, determining from the main axes a major axis having a major-axis orientation, computing a geometrical center and a center of mass of the finger-data map, computing an eccentricity of the finger-data map as a function of the lengths of the main axes outputting the major-axis orientation as indicative of the finger-orientation direction in the plane of the screen, outputting the mutual position of the geometrical center and the center of mass of the finger-data map as indicative of finger-pointing direction along the finger-orientation direction in the plane of the screen, and outputting a combination of the eccentricity and the area of the finger data map as indicative of finger orientation with respect to the plane of the screen.

Method and system for finger sensing, related screen apparatus and computer program product

Detecting the presence of a finger in proximity of a screen that generates detection signals in the horizontal direction and vertical direction includes sampling the detection signals and generating raw-data vectors X and Y. The raw data have a maximum for elements of the vector that define the position of the finger on the screen in the directions X and Y, respectively. The vectors X and Y are divided into subsets defined as 'macro-areas' and cumulative values computed of each macro-area by adding together all the elements of the vector X and of the vector Y that belong to the macro-area. The maximum values are selected from among horizontal cumulative values and vertical cumulative values. A value identifying the macro-area selected on the basis of the maximum values is supplied, or no value supplied in the presence of elements of disturbance in the proximity of the screen.

Method and system for detecting the presence of a finger or a hand in the proximity of a touchless screen, corresponding screen device, and corresponding computer program product

An embodiment of a method of recognizing finger detection data in a detection data map produced by a touch screen includes converting the data from the x, y, z space into a three-descriptor space including: a first coordinate representative of the number of intensity peaks in the map, a second coordinate representative of the number of nodes (i.e., pixels) absorbed under one or more of the intensity peaks. A third coordinate may be selected as the angular coefficient or slope of a piecewise-linear approximating function passing through points having the numbers of nodes absorbed under the intensity peaks ordered in decreasing order over said intensity peaks, which permits singling out finger data with respect to non-finger data over the whole of the touch screen. The third coordinate may be also selected as an adjacency value representative of the extent the intensity peaks are adjacent to one another, which permits singling out finger data produced over a portion of the touch screen with respect to non-finger data produced over another portion of the touch screen.

Method and system for touch shape recognition, related screen apparatus, and computer program product

In one embodiment, a light sensor includes four cell arrays, one for each color of the Bayer pattern, and four lenses each focusing the light coming from the scene to be captured on a respective cell array. The lenses are oriented such that at least a second green image, commonly provided by the fourth cell array, is both horizontally and vertically shifted (spaced) apart by half a pixel pitch from a first (reference) green image. In a second embodiment, the four lenses are oriented such that the red and blue images are respectively shifted (spaced) apart by half a pixel pitch from the first or reference green image, one horizontally and the other vertically, and the second green image is shifted (spaced) apart by half a pixel pitch from the reference green image both horizontally and vertically.

Compound camera sensor and related method of processing digital images

A method of processing and device configure to process digital images to enhance image quality and correct motion blur. A number N of images of a scene are captured with an exposure time T. An order of sharpness of the images is determined and the sharpest image is used as a reference image for generating an output image.

Method of merging images and relative method of generating an output image of enhanced quality

A digital image processing system and method for removing motion effects from images of a video sequence, and generating corresponding motion compensated images.

Method of generating motion vectors of images of a video sequence

A method is provided for obtaining an image with a large dynamic range. An image is acquired such that each image pixel is represented by a plurality of values obtained at the same time but for different integration levels (effective exposures). For each pixel, a representative value is selected among those available, such that it is neither saturated nor blackened.

Method for acquiring a digital image with a large dynamic range with a sensor of lesser dynamic range

A method of processing digital images to reduce the effects of color bleeding. Chrominance components for pixels in a working window are determined and weights are assigned to the pixels in the working window. A chrominance correction for a center pixel in the working window is generated based on the chrominance components and the assigned weights. Fuzzy variables and thresholds may be applied to generate the assigned weights and the chrominance correction.

Reduction of color bleeding effects in a digitally processed image

A luminance intensity of pixels of an input digital image is corrected for generating a corrected digital image. A luminance of each pixel is calculated as a function of the luminance of a corresponding pixel in an original image according to a parametric function. A mask of the input digital image to be corrected is generated according to a bilateral filtering technique. For each pixel of the input digital image, a respective value of at least one parameter of the parametric function is established based upon the luminance of a corresponding pixel of the mask.

Method for correcting a digital image

Digital video signals, such as the signals generated by an image sensor in a Bayer format, are converted into an encoded format. In the Bayer format, the pixels of each line are alternately coded with two colors, and then converted into the encoded format. In the encoded format, the pixels of the digital video signals are reordered into sets of adjacent pixels, such that the sets group pixels coded with the same color. The encoded signal data results in a reduced switching activity when transmitted over a bus.

Process and system for processing signals arranged in a bayer pattern

In the method, the membership image is produced through a multi-stage process that contemplates a first punctual classification stage generating a rough membership image, followed by a low-pass filtering of regionalization of the image through a down-sampling of the image followed by an up-sampling of the image, and in a further step of merging the regions that overcomes the superposition effects induced by the low-pass filtering operation. The so generated membership image contains semantic information of the input image that may be used for effectively implementing an adaptive correction/improvement of the color of the input image. For an adaptive correction/improvement of the color, the encoded data of the generated membership image is fed in parallel to the data of the real image to an adaptive modification block of the color of the image pixels.

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Gravina di Catania, Italy

Alessandro Capra