Adeia Semiconductor Bonding Technologies Inc.

Fotonation Limited

Fotonation Vision Limited

Tessera Technologies Ireland Limited

Digitaloptics Corporation Europe Limited

Corneliu Florea

Peter Corcoran

Adrian Zamfir

Felix Albu

Mihai Ciuc

Adrian Dorin Capata

Eran Steinberg

Vlad Poenaru

Petronel Bigioi

Yury Prilutsky

Alexandru Drimbarean

Alexei Pososin

Valentin Mocanu

Cosmin Nicolae Stan

Razvan G Condorovici

Foti Coleca

Andreea Oana Miu

Ruxandra Vränceanu

Dan Miss

Ruxandra Vrânceanu

Razvan George Condorovici

Vladimir Poenaru

A biometric recognition system for a hand held computing device incorporating an inertial measurement unit (IMU) comprising a plurality of accelerometers and at least one gyroscope is disclosed. A tremor analysis component is arranged to: obtain from the IMU, accelerometer signals indicating device translational acceleration along each of X, Y and Z axes as well as a gyroscope signal indicating rotational velocity about the Y axis during a measurement window. Each of the IMU signals is filtered to provide filtered frequency components for the signals during the measurement window. The accelerometer signals are combined to provide a combined filtered accelerometer magnitude signal for the measurement window. A spectral density estimation is provided for each of the combined filtered accelerometer magnitude signal and the filtered gyroscope signal. An irregularity is determined for each spectral density estimation; and based on the determined irregularities, the tremor analysis component attempts to authenticate a user of the device.

Biometric recognition system

Sub-regions within one or more face images are identified within a digital image, and enhanced by applying an artificial glint symmetrically and/or synchronously to image data corresponding to sub-regions of eyes within the face image. An enhanced face image is generated including an enhanced version of the face that includes certain original pixels in combination with pixels corresponding to the one or more eye regions of the face with the artificial glint.

Eye beautification under inaccurate localization

An estimated total camera motion between temporally proximate image frames is computed. A desired component of the estimated total camera motion is determined including distinguishing an undesired component of the estimated total camera motion, and including characterizing vector values of motion between the image frames. A counter is incremented for each pixel group having a summed luminance that is greater than a threshold. A counter may be decremented for pixels that are under a second threshold, or a zero bit may be applied to pixels below a single threshold. The threshold or thresholds is/are determined based on a dynamic luminance range of the sequence. The desired camera motion is computed including representing the vector values based on final values of counts for the image frames. A corrected image sequence is generated including the desired component of the estimated total camera motion, and excluding the undesired component.

Fast motion estimation method

Two or more digital images of a same scene are captured with different exposure levels. Image pairs are generated that have a same exposure level from the image data of differently exposed images by adjusting the exposure of at least one of the pair of images. A ghosting map is generated based on differences between the pair of images adjusted to the same exposure. A blurred ghosting map is generated and alpha blending is performed.

Dynamic range extension by combining differently exposed hand-held device-acquired images

Sub-regions within a face image are identified to be enhanced by applying a localized smoothing kernel to luminance data corresponding to the sub-regions of the face image. An enhanced face image is generated including an enhanced version of the face that includes certain original pixels in combination with pixels corresponding to the one or more enhanced sub-regions of the face.

Automatic face and skin beautification using face detection

A method and apparatus for providing image processing. For one embodiment of the invention, an image processing apparatus is arranged to process a first relatively underexposed and sharp image of a scene, and a second relatively well exposed and blurred image, nominally of the same scene, the first and second images being derived from respective image sources. The apparatus provides a portion of the relatively first underexposed image as an input signal to an adaptive filter; and a corresponding portion of the second relatively well exposed image as a desired signal to the adaptive filter. The adaptive filter produces an output signal from the input signal and the desired signal; and an image generator constructs a first filtered image from the output signal, relatively less blurred than the second image.

Image processing method and apparatus

A technique is provided for generating sharp, well-exposed, color images from low-light images. A series of under-exposed images is acquired. A mean image is computed and a sum image is generated each based on the series of under-exposed images. Chrominance variables of pixels of the mean image are mapped to chrominance variables of pixels of the sum image. Chrominance values of pixels within the series of under-exposed images are replaced with chrominance values of the sum image. A set of sharp, well-exposed, color images is generated based on the series of under-exposed images with replaced chrominance values.

Tone mapping for low-light video frame enhancement

An adaptive motion estimation and deblurring technique for acquired digital images includes acquiring multiple digital images with a moving digital image acquisition device that includes an image sensor, including a relatively sharp, underexposed reference image and a blurred image. Anb initial approximate point spread function (PSF) is estimated corresponding to the moving of the device. A different DC offset point is determined and a second PSF is calculated based on the different DC offset point.

Adaptive PSF estimation technique using a sharp preview and a blurred image

Eye beautification

An image acquisition sensor of a digital image acquisition apparatus is coupled to imaging optics for acquiring a sequence of images. Images acquired by the sensor are stored. A motion detector causes the sensor to cease capture of an image when the degree of movement in acquiring the image exceeds a threshold. A controller selectively transfers acquired images for storage. A motion extractor determines motion parameters of a selected, stored image. An image re-constructor corrects the selected image with associated motion parameters. A selected plurality of images nominally of the same scene are merged and corrected by the image re-constructor to produce a high quality image of the scene.

Image acquisition method and apparatus

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Bucharest, Romania

Corneliu Florea