Hewlett-packard Development Company, L.p.

Prakash D Reddy

Craig Peter Sayers

James Allely Rowson

Eamonn O'Brien-Strain

George H Forman

Kave Eshghi

Steven Rosenberg

Robert Nelson Mayo

Jian Fan

Rajan Mathew Lukose

Yuhong Xiong

Andrew Bolwell

Jayakumar Suthira

Dudekula Shariff

Robert D Shur

Yuhon Xiong

Deivanayagam Ramakrishnan

Prabodh Tiwari

In one example, an executable program on a computer-readable storage medium that instructs a processor to predict a characteristic of at least some parts in plural orders from a corresponding computer model of the part. The program also instructs the processor to assign, based on the predicted characteristics, models of at least some similar parts from different orders to different build trays usable to fabricate the parts. The program further instructs the processor to, for each build tray, sort the fabricated parts into the plural orders by matching a measured characteristic of a part to a predicted characteristic of unsorted parts from the build tray.

Build tray model assignment and fabricated part sorting

In one example implementation, a system for ranking target dimensions includes a model engine to generate a three-dimensional (3D) model of an object from a scan of the object, an analysis engine to analyze the 3D model of the object and determine target dimensions of the object, a ranking engine to rank the target dimensions based on target dimension characteristics, historical scan information related to the target dimension characteristics, or a combination thereof, and a display engine to display information relating to the ranked target dimensions of the object.

Ranking target dimensions

Examples disclosed herein relate to a three-dimensional object to be displayed on a browser. Examples include to acquire, from a remote system, a three-dimensional object to be displayed in a browser of a computing device. The computing device to display an active region edit interface on the browser. The computing device to acquire an edit request for an active region of the three-dimensional object in the active region edit interface. The computing device to provide, to the remote system, the edit request for the active region of the three-dimensional object. The computing device to acquire, from the remote system, an edited three-dimensional active region corresponding to the edit request for the active region. The computing device to display the edited three-dimensional active region as part of the three-dimensional object on the browser.

Display three-dimensional object on browser

According to an example, an operation on a version of an electronic content may be performed and a determination as to whether the operation is an editing operation may be made. In response to the operation being an editing operation, a new version may be created and information pertaining to the performance of the operation on the new version may be recorded. In addition, for each significant version, information pertaining to the significant version may be displayed, in which the information may include an identification of the significant version, available operations on the significant version, and a last operation performed on the significant version, in which a significant version may include a version in which no editing operations have been applied or a version in which an operation that is visible to another user has been performed on the version and the operation is outstanding.

Electronic content information display management

An average size of a plurality of page images is determined, and a size of a first one of the page images is determined. The size of the first page image is compared to the average size. If the size of the first page image is larger than the average size by a first predetermined amount and larger than the average size by less than a second predetermined amount, then the first page image is rotated for printing. If the size of the first page image is larger than the average size by at least the second predetermined amount, then the first page images divided into multiple pages for printing.

Page image treatment

Data representing an image of text is received, as is data representing the text in non-image form. A valid content boundary within the image of the text is determined. For each character within the text in the non-image form, a location of the character within the image of the text is determined. Where the location of the character within the image of the text falls outside the valid content boundary, the character is removed from the data representing the text in the non-image form.

Removing character from text in non-image form where location of character in image of text falls outside of valid content boundary

Systems and methods for replacing non-image text are provided. One method for replacing non-image text includes padding a first data representing an image of text to create an image segment. The method includes replacing a second data representing non-image text with the image segment.

Systems and methods for replacing non-image text

In one embodiment, a digitized document, formatted as an image file and representing a scanned original page with a page boundary, is received. An image resolution for the digitized document is identified. A height and width of the page boundary, measured in pixels, is identified. A desired trim size for the digitized document is determined based on a function of the identified page boundary height and width and the image resolution. An available trim size that is closest to the desired trim size is selected for printing of the digitized document, via data indicative of available trim sizes stored in a computer-readable medium.

Method and system to select a trim size

Locations of word images corresponding to words in a document image are ascertained. The word images are grouped into clusters. For each of multiple of the clusters, a respective compressed word image cluster is determined based on a joint compression of respective ones of the word images that are grouped into the cluster. The positions of the word images in the document image are associated with the respective ones of the compressed word image clusters corresponding to the clusters respectively containing the word images.

Word-based document image compression

An image of a known text sample having a text type is generated. The image of the known text sample is input into each OCR engine of a number of OCR engines. Output text corresponding to the image of the known text sample is received from each OCR engine. For each OCR engine, the output text received from the OCR engine is compared with the known text sample, to determine a confidence value of the OCR engine for the text type of the known text sample.

Optical character recognition (OCR) engines having confidence values for text types

A page of a digitally scanned document and graphical user interface elements (GUI) are displayed. Each GUI element corresponds to a potential flaw within the page and includes an example image of the potential flaw. After the GUI elements are displayed, a user is permitted to select a user-detected flaw present within the page of the digitally scanned document by selecting one of the GUI elements.

User selection of flaw present within digitally scanned document

A system and method is disclosed for removing artifacts from a digitized document. The method discloses receiving a digitized document, having an image format, and including content and an artifact; identifying a content boundary within the digitized document; enhancing the digitized document after identifying the content boundary; and removing the artifact by cropping the digitized document to the content boundary after enhancing the digitized document The system discloses a processor configured to operate a series of functional modules, including: a means for receiving a digitized document, having an image format, and including content and an artifact; a content boundary identification module, for identifying a content boundary within the digitized document; an image enhancement module, for enhancing the digitized document after identifying the content boundary; and a content cropping module, for removing the artifact by cropping the digitized document to the content boundary after enhancing the digitized document.

System and method for removing artifacts from a digitized document

Techniques for performing an incremental update to a set of hierarchically structured information that do not expose the structure and content of the hierarchically structured information to unauthorized parties. The present techniques include encrypting the hierarchically structured information such that an arrangement of nodes and corresponding data of the hierarchically structured information is not exposed and each node includes a corresponding node identifier that is not encrypted and updating the hierarchically structured information by referring to the nodes using the node identifiers.

Secure incremental updates to hierarchicaly structured information

Illustrated is a system and method to prepare for display, within a Graphical User Interface (GUI), a subset selection pane, an icon and summary pane, and a sort pane. The system and method further to include to prepare for display, within the icon and summary pane, a result set that includes an icon representing a three dimensional book and a textual summary of the book. The system and method also includes enabling a screen object, within the subset selection pane, to receive input to select a subset of the result set to be displayed within the icon and summary pane. Further, the system and method includes enabling a screen object, within the sort pane, to receive input to select the subset of the result set to be sorted and displayed within the icon and summary pane.

Rendering and sorting book search results as three dimensional icons

The present disclosure provides a computer-implemented method of translating an image-based electronic document into a text-based electronic document. The method includes electronically scanning an image-based document to determine positions of word images in the image-based document. The method also includes extracting the word images from the image-based document and storing the word images to an electronic storage device. The method also includes grouping a subset of the word images into a word cluster based on a similarity of the word images, wherein the word images in the word cluster correspond to a same actual word. The method also includes generating a character-encoded transcription for the word cluster based on the word images in the word cluster. The method also includes adding the character-encoded transcription to a text-based electronic document at locations corresponding to the positions of the word images in the image-based document.

Growing community of inventors

Palo Alto, CA, United States of America

Prakash D Reddy