Abstract:
A manual windowing with auto-segmentation assistance method and system are disclosed that include defining manual tags to be assigned to one or more windows via a tag selection module, assigning the defined manual tags to the one or more windows via a manual tag assignment module and auto-segmenting the one or more windows within the display medium by producing auto-segmentation tags via the auto-segmentation module. Furthermore the method and system according to this invention provide for mapping tags to the auto-segmentation tags via a tag mapping module and merging the manual tags and the auto-segmentation tags via a merging module.
Abstract:
An image forming device includes a backing and is arranged for a media to be positioned against the backing. The backing includes an embedded backing pattern. The media is skewed with respect to the scanning, thus defining a media skew. The media and the backing are scanned to form a pixel pattern. For each pixel, an included pattern recognition algorithm determines when the pixel represents the backing. When the pixel represents the backing, it is replaced with a replacement backing symbol, otherwise it is replaced with a replacement media symbol. The pixel determining and symbol replacing process is continued for remaining pattern pixels to form a replacement symbol pattern comprised of the replacement backing symbols and the replacement media symbols. The media is then processed based on the replacement symbol pattern, the processing including detecting the media skew, registering the media, or both.
Abstract:
Disclosed methods and systems perform electronic registration of digitally captured images in real-time and performs accurate and robust digital image processing by analyzing the entire digitally captured image.
Abstract:
The present invention is a method and apparatus for processing image data to accomplish tuning or adjustment of images, so as to modify at least the darkness thereof, using compact, efficient methods and designs.
Abstract:
A system and method for processing segmentation tags is disclosed. The system comprises a neighborhood analysis module, transition analysis module, and a tag cleaning module. The neighborhood analysis module generates a neighborhood block tag prediction from a block of segmentation tags having a first predefined relationship with a current tag. The transition analysis module generate a transition block tag prediction from a block of segmentation tags having a second predefined relationship with the current tag. The tag cleaning module modifies selected segmentation tags based on the neighborhood block tag prediction and the transition block tag prediction. The method comprises identifying a current segmentation tag to be cleaned; generating a tag prediction from a plurality of segmentation tags having a predefined relationship to the current segmentation tag; and generating a cleaned segmentation tag for the current segmentation tag based upon the current segmentation tag and the tag prediction.
Abstract:
A method and apparatus for digital image processing are provided for controlling luminance channel overshoot in response to FIR or other enhancement processing based upon chrominance. The luminance value of the enhanced digital image data for each pixel of an image is compared to corresponding local minimum and maximum luminance values of the non-enhanced image obtained from the neighborhood of the subject pixel. If an enhanced luminance value for a subject pixel falls outside the corresponding local minimum/local maximum luminance value range by a positive or negative overshoot amount, the enhanced luminance value is adjusted to attenuate the overshoot amount. The amount by which the enhanced luminance value for an enhanced pixel is adjusted varies depending upon the chrominance of the enhanced pixel. Also, the amount of overshoot attenuation can vary depending upon whether the enhanced luminance value is greater than the local maximum luminance value or less than the local minimum luminance value.
Abstract:
The present invention provides a method and apparatus for classifying image data. A video average may be determined from the image data. Peak detection may then be limited to an area within the image data where the video average is above a first threshold. Valley detection may be limited to an area where the video average is below a second threshold.
Abstract:
A method and apparatus are provided for classifying image data. A peak/valley detection device may count peaks and valleys within a window. A local roughness of the image data may be determined and the data may be classified based on the peak/valley count and the local roughness.
Abstract:
The invention discloses an assembly type negative pressure isolation chamber, in which the necessary configuration of the negative pressure isolation ward is contained in a hexahedral chamber. The chamber forms an independent building assembly unit, which can be integrated into or removed from the building system. The chamber can also be disassembled and transported, and the switching of use functions can be realized through the flexible combination and simple modification of components. The indoor wall of the chamber is light Clean and washable materials are integrated with furniture. The air conditioning system adopts internal circulation return air and independent temperature regulating device. The sewage pre disinfection link is added to the sewage system. The negative pressure isolation chamber can help the medical isolation building system expand rapidly in case of respiratory infectious disease outbreak and can carry out space mobility with the transfer of the epidemic situation.
Abstract:
Some embodiments are directed to a method of automatically modifying a scanned image of a page from an input document comprising a plurality of pages. First, scanned images of the plurality of pages are obtained. Next, a user selection for an output orientation of an output document and optionally value of N for an N-Up operation is received. Thereafter, input orientation of each scanned image is detected. Then, the scanned image is rotated, based on the detected input orientation, the output orientation and the value of ‘N’ if provided by the user. Next, the rotated scanned image content is resized so that it fits on a page. Finally, the output document is prepared that includes pages in the output orientation.