A data decoding system that includes a server-side proxy component and at least two back-end computers, where the server-side proxy component is configured, when it receives an encoding request from a client, to select a back-end computer to forward the encoding request to, based on either a pre-defined rule, load estimates for the at least two computers, estimated network throughputs across network paths to the two computers. In response to receiving this request, the back-end computer that is selected is configured to encode the request.

Hand held bar code readers or mobile computers with cloud computing services

A data decoding system can comprise one or more computers communicatively coupled to a network. The computers can execute at least one decoding process. The decoding process can be configured, responsive to receiving a decoding request comprising an image of decodable indicia, to locate the decodable indicia within the image, and to decode the decodable indicia into a decoded message. The decoding process can be further configured, responsive to completing a decoding operation, to transmit to the client the decoded message and/or the decoding operation completion code.

Cloud-based system for reading of decodable indicia

The method defines a user environment based on detected motion data and/or ambient noise data. The user environment is then used to apply an appropriate audio adjustment mode. In one embodiment, the user environment definition further includes location data. In one embodiment, the location data is obtained from one of: a global positioning system (GPS), and network triangulation.

Method and Apparatus for Adjusting Audio for a User Environment

Systems and methods are described for generating restricted depth of field depth maps. In one embodiment, an image processing pipeline application configures a processor to: determine a desired focal plane distance and a range of distances corresponding to a restricted depth of field for an image rendered from a reference viewpoint; generate a restricted depth of field depth map from the reference viewpoint using the set of images captured from different viewpoints, where depth estimation precision is higher for pixels with depth estimates within the range of distances corresponding to the restricted depth of field and lower for pixels with depth estimates outside of the range of distances corresponding to the restricted depth of field; and render a restricted depth of field image from the reference viewpoint using the set of images captured from different viewpoints and the restricted depth of field depth map.

Systems and Methods for Synthesizing Images from Image Data Captured by an Array Camera Using Restricted Depth of Field Depth Maps in which Depth Estimation Precision Varies

Methods for detecting defective pixels in imaging arrays involve establishing probabilities that individual pixels are defective and updating those probabilities by analysing images acquired by the imaging arrays. Probabilities may be evaluated for each of two or more defect conditions. The methods may be used to detect defects such as stuck-low, stuck-high, high-sensitivity, low sensitivity, hot, and defect-free conditions. Other more complicated defect conditions can also be detected. Apparatus for detecting defective pixels may be integrated with a camera or other imaging device or provided separately.

Methods and apparatus for detecting defects in imaging arrays by image analysis

Rather than storing a table within a digital camera or other optical device of defective pixels within its image sensor, defective pixels are dynamically identified by comparing the output values of individual pixels under test with those of neighboring pixels. If the neighbors are all above or below the pixel under test by a defined threshold amount, the output of the pixel under test is replaced with a value calculated from the outputs of neighboring pixels.

Dynamic Identification and Correction of Defective Pixels

Video data of successive image frames are processed in a digital camera or other video image data acquisition device immediately after acquiring the video data, or during post-processing of the video data at some time after acquiring the video data, to reduce the effects of unintended motion (jitter) of the hand-held devices by stabilizing the images A processing circuit used to calculate an estimate of motion between components of successive image frames as part of a MPEG-4 or other compression algorithm is also used to estimate motion upon which the video data are altered to stabilize the images The individual images may be pre-stabilized by using the results of stabilizing a prior image in order to reduce the amount of processing necessary to stabilize a current image

Processing of video data to compensate for unintended camera motion between acquired image frames

A self-tuning clock recovery phase-locked loop (PLL) includes a programmable divide-by-M, a phase-frequency detector, a programmable voltage-controlled oscillator (VCO), a programmable divide-by-N, and a PLL tuning circuit, which in normal mode operation, perform as a conventional PLL. When the frequency of an input clock signal to the PLL changes by more than a threshold value, however, the PLL tuning circuit causes the PLL to be retuned for the new frequency by adjusting offset and gain parameters in the PLL such that the input voltage to the VCO is mid-way in its input voltage range when the output clock frequency of the PLL is approximately equal to the input clock frequency multiplied by a closed loop gain of the PLL, so that the VCO is operating in a linear region having wide dynamic frequency range.

Self-tuning clock recovery phase-locked loop circuit

A method and device are provided for method for stabilization of image data by an imaging device. In one embodiment, a method includes detecting image data for a first frame and a second frame, performing motion estimation to determine one or more motion vectors associated with global frame motion for image data of the first frame, performing an outlier rejection function to select at least one of the one or more motion vectors, and determining a global transformation for image data of the first frame based, at least in part, on motion vectors selected by the outlier rejection function. The method may further include determining a stabilization transformation for image data of the first frame by refining the global transformation to correct for unintentional motion and applying the stabilization transformation to image data of the first frame to stabilize the image data of the first frame.

Method and apparatus for image stabilization

Techniques for modifying data of an image that can be implemented in a digital camera, video image capturing device and other optical systems are provided to correct for Image image shading variations appearing in data from a two-dimensional photo-sensor. These variations can be caused by imperfect lenses, non-uniform sensitivity across the photo-sensor, and internal reflections within a housing of the optical system, for example. In order to correct for these variations, a small amount of modification data is stored in a small memory within the camera or other optical system, preferably separate correction data for each primary color. Image data from individual pixels are corrected on the fly by interpolating individual pixel corrections from the stored modification data, at the same rate as the image data is being acquired, so that the correction takes place without slowing down data transfer of picture data from the image sensor.

Victor Pinto

Papers

Dynamic Identification and Correction of Defective Pixels

Processing of video data to compensate for unintended camera motion between acquired image frames

Self-tuning clock recovery phase-locked loop circuit

Method and apparatus for image stabilization

Techniques of modifying image field data by extrapolation