Hp Indigo B.v.

Avi Malki

Oren Haik

Oded Perry

Liron Itan

Alexander Spivakovsky

Eli Chen

A first separation distance is determined between a first pair of defects in a scanned image of a first printed sheet, and a second separation distance is determined between a second pair of defects in a scanned image of a second printed sheet. The defects are determined as having a separation distance in that the first and second separation distances are each within a first threshold of a specified separation distance and/or a difference between the first and second separation distances is below a second threshold. A source of the defects can be determined based on the characteristic separation distance.

Determining defects having a characteristic separation distance

In one example of the disclosure, a set of scanned images is accessed. The scanned images are scans of distinct printouts of subject images produced utilizing an intermediate transfer member. A set of defect maps is created by comparing the scanned images to reference data for the subject images. The set of defect maps are combined into an integrated defect map. A dent defect on the ITM is identified utilizing the integrated defect map.

ITM dent identification utilizing integrated defect maps

A method for processing an image is disclosed. The method may include obtaining a target image to be printed using print agent in a printable area of a substrate of a particular colour. The method may include obtaining a scanned image of a substrate on which the target image has been printed, the substrate being of the particular colour. The method may include determining, from the scanned image, the particular colour of the substrate. The method may include using the target image as a reference image against which the scanned image is to be compared. The method may include adjusting a colour in the reference image according to the determined particular colour of the substrate. An apparatus and a machine-readable medium are also disclosed.

Adjusting a colour in an image

In an example, a method includes determining, by a processor, a cumulative indication of defects present in linear sub-portions located in a common position of each of a plurality of substrate sheets bearing a printed image. The method may further comprise identifying, by the processor, a linear defect based on the cumulative indication of defects.

Identifying linear defects

In an example, a method includes determining, by a processor, at least one separation distance between defects in a scanned image of a printed substrate sheet bearing a printed image, wherein the separation distance determined in a predetermined direction. The method may further comprise determining, by the processor, if the defects have a characteristic separation distance.

In one example of the disclosure, a set of scanned images is accessed. The scanned images are scans of distinct printouts of subject images produced utilizing a photo imaging plate. A set of defect maps is created by comparing the scanned images to reference data for the subject images. The set of defect maps are combined into an integrated defect map. A scratch defect on the PIP is identified utilizing the integrated defect map.

Scratch identification utilizing integrated defect maps

Apparatus to detect a defect in a printed image and methods of detecting detects in a printed image are described. In some examples, a printing operation is initiated using image data to generate a printed image. The printed image is then scanned to generate a scanned image. A resolution of the scanned image is estimated, calculated or determined on the basis of a characteristic of the printing operation, and a reference image, having a resolution corresponding to the estimated, calculated or determined resolution, is generated from the image data. Whether defects are present in the printed image may be determined on the basis of a comparison of the reference image with the scanned image.

Image defect detection

Streaks in images are detected by determining a rotation angle of an image and calculating a rotated image based on a rotation of the image by the rotation angle. A cross-sectional pixel profile of the rotated image is determined and a peak in the cross-sectional pixel profile of the rotated image is determined. A streak in the image is identified based on the determined peak.

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Ness Ziona, Israel

Avi Malki