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1402 results about "Single pixel" patented technology

Biometric piezo scanner

A piezoelectric thin film sensor array is used to scan and capture biometric data, for example, a fingerprint image. In one embodiment, a multi-layer structure includes a PVDF layer in between two conductor grids arranged orthogonally to one another. Urethane can be added to one side where a finger is placed. A foam substrate can be used as a support. In one feature, the PVDF, and grids can be peeled off like a label for easy replacement. Multiplexers are switched to scan the sensor. A single pixel or a group of pixels can be detected and output to an image memory. The presence of a fingerprint ridge is detected by virtue of a ring-down oscillation that arises from reflection when an electric field is applied to the piezoelectric thin film sensor array at a pixel in contact with the fingerprint ridge. For example, such a ring-down value associated with a fingerprint ridge can be detected at about 150 ns. (or 5 cycles at 30 MHZ). Other reflections indicative of additional biometrics (e.g. from tissue, blood, bone, fingernail, etc.) can also be detected. A Doppler effect due to reflections from circulating blood can also be detected. Such a Doppler effect can provide further information about direction and speed of blood circulation. An instantaneous pyroelectric effect can also be detected to indicate a live finger presence.
Owner:SONAVATION INC

System and method for processing non-linear image data from a digital imager

A system and method process non-linear image data, still or video, from a digital imager. Noise generated by analog-to-digital converters is filtered from a pixel of digital image data. Moreover, the effects of single pixel defects in the imager are eliminated by clamping a predetermined pixel of image data within the window when the value of the predetermined pixel is greater than a maximum value of the image data of neighboring pixels or less than a minimum value of the image data of neighboring pixels. Ripples in image data are reduced by eliminating the effects of single pixel defects before filtering for crosstalk caused by electrical crosstalk between sensor elements in an imager. Dark current is removed from image data generated by an imager by subtracting a fraction of a determined dark current value from all image data generated by the imager to compensate for nonlinearities in dark current across the imager. The image data is white balanced by creating a set of scalar color adjustments from determined average color values and constraining the set of scalar adjustments to plausible lighting conditions to prevent overcompensation on images having large regions of similar hue. Lastly, utilization of a fixed set of intensity levels is optimized by remapping and restreching the image data to create new luma values for each pixel.
Owner:SMAL CAMERA TECH

Converting low-dose to higher dose 3D tomosynthesis images through machine-learning processes

A method and system for converting low-dose tomosynthesis projection images or reconstructed slices images with noise into higher quality, less noise, higher-dose-like tomosynthesis reconstructed slices, using of a trainable nonlinear regression (TNR) model with a patch-input-pixel-output scheme called a pixel-based TNR (PTNR). An image patch is extracted from an input raw projection views (images) of a breast acquired at a reduced x-ray radiation dose (lower-dose), and pixel values in the patch are entered into the PTNR as input. The output of the PTNR is a single pixel that corresponds to a center pixel of the input image patch. The PTNR is trained with matched pairs of raw projection views (images together with corresponding desired x-ray radiation dose raw projection views (images) (higher-dose). Through the training, the PTNR learns to convert low-dose raw projection images to high-dose-like raw projection images. Once trained, the trained PTNR does not require the higher-dose raw projection images anymore. When a new reduced x-ray radiation dose (low dose) raw projection images is entered, the trained PTNR outputs a pixel value similar to its desired pixel value, in other words, it outputs high-dose-like raw projection images where noise and artifacts due to low radiation dose are substantially reduced, i.e., a higher image quality. Then, from the “high-dose-like” projection views (images), “high-dose-like” 3D tomosynthesis slices are reconstructed by using a tomosynthesis reconstruction algorithm. With the “virtual high-dose” tomosynthesis reconstruction slices, the detectability of lesions and clinically important findings such as masses and microcalcifications can be improved.
Owner:ALARA SYST

Character picture verification code identifying method based on identification feedback

The invention provides a character picture verification code identifying method based on identification feedback. The character picture verification code identifying method is characterized by comprising the following steps of: firstly, converting an original colorful image into a gray level image and carrying out binaryzation treatment to obtain binaryzation image data; then, repairing a binaryzation image, removing image edge burrs and filling a central blank; finishing the connection of broken strokes to obtain a repaired image; removing a background and an interference point or line of the repaired image to obtain a noise-free image; thinning the noise-free image to obtain a thinned image with a single pixel; then, cutting the thinned image to obtain a single-character image which only contains a single character; and finally, carrying out normalization on the single-character image and identifying the character. According to the character picture verification code identifying method based on the identification feedback, a corresponding algorithm is designed to process a character picture identification code including various types of noises and having the phenomena that the character is stuck, inclined, rotated, deformed and the like, so as to finish high-efficiency and high-precision identification. The character picture verification code identifying method based on the identification feedback can be applied to verification code identification in an automatic program.
Owner:SHANGHAI TRUELAND INFORMATION & TECH CO LTD
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