Abstract: The present invention is directed to novel heterodimeric antibodies.

Abstract: A method of optimizing printing is applied to a printing apparatus and has following steps of retrieving an input image, executing a tagging process on the input image for tagging one of an edge tag, a fuzzy tag, and a photo tag on each sub-image of the input image, executing the different printing converting process on each sub-image according to its tag for obtaining a printable image, and printing according to the printable image. The present disclosed example can deepen the object edges in the image being printed, improving the image quality of non-edge regions, and improving the printing quality.

Abstract: A method of optimizing printing is applied to a printing apparatus and has following steps of retrieving an input image, executing a tagging process on the input image for tagging one of an edge tag, a fuzzy tag, and a photo tag on each sub-image of the input image, executing the different printing converting process on each sub-image according to its tag for obtaining a printable image, and printing according to the printable image. The present disclosed example can deepen the object edges in the image being printed, improving the image quality of non-edge regions, and improving the printing quality.

Abstract: Various embodiments are directed to methods, systems, and devices for improving the quality of image data for printing by a printer having relatively low resolution capabilities. Image data may be scanned, captured or otherwise received. The image data may be received in bands, chunks, blocks, portions, regions, or its entirety. An edge detector is subsequently employed to detect a location of edges in a region of the received image data. For image data pixels that are located in or close to a detected edge, a first screen is applied to modify these pixels to compensate for printing at or near the detected edge. Otherwise, a second image screen is applied to modify pixels for printing that are not close to a detected edge. The first screen may be an error diffusion screen or a threshold screen. The second screen may be a halftone screen.

Abstract: Embodiments are directed towards identifying background pixels in a scanned image so that they can be removed from the image. A histogram of each color channel for an initially scanned portion of the image may be determined. The histogram may represent a frequency distribution of pixels in the scanned portion across each color value for each color channel. A white point tracking profile may be determined based on the histogram. The white point tracking profile may identify a range of color values for each channel that are statistically related to a mode color value of a corresponding color channel. When pixels in the scanned image are determined to have a color profile within the white point tracking profile, then those pixels may be modified to a predetermined color profile, such as a maximum color value for each channel. The modified pixels may then be removed from the scanned image.

Abstract: Embodiments are directed towards identifying background pixels in a scanned image so that they can be removed from the image. A histogram of each color channel for an initially scanned portion of the image may be determined. The histogram may represent a frequency distribution of pixels in the scanned portion across each color value for each color channel. A white point tracking profile may be determined based on the histogram. The white point tracking profile may identify a range of color values for each channel that are statistically related to a mode color value of a corresponding color channel. When pixels in the scanned image are determined to have a color profile within the white point tracking profile, then those pixels may be modified to a predetermined color profile, such as a maximum color value for each channel. The modified pixels may then he removed from the scanned image.