摘要:
A system resizes content within a document that includes a document segmenter that receives a document that contains content. The document segmenter analyzes the content within the document and segments the content into a plurality of object types. An object priority applicator determines a class value associated with each object type. A location scaler identifies a datum point for each object type within the document, wherein each datum point maintains a relative location to one another regardless of document resizing. An object sizing component resizes each object based at least in part upon the class value.
摘要:
What is disclosed is a resizing method that utilizes segmentation information to classify objects found within a document and then selects the most appropriate resizing technique for each identified object. The present method employs readily available document parsers to reliably extract objects. e.g. text, background, images, graphics, etc., which compose the document. Information obtained from a document parser is utilized to identify the document components for classification. The extracted objects are then classified according to their object type. Each of classified objects are then resized using a resizing technique having been pre-selected for the object type based on their respective abilities to resize certain types of document content over other resizing techniques. The present method advantageously extends smart or content-based scaling and is especially useful for N-up or variable-information printing. The present method finds its intended uses in enhancing N-up and handout options currently provided in a variety of print-drivers.
摘要:
What is disclosed is a resizing method that utilizes segmentation information to classify objects found within a document and then selects the most appropriate resizing technique for each identified object. The present method employs readily available document parsers to reliably extract objects. e.g. text, background, images, graphics, etc., which compose the document. Information obtained from a document parser is utilized to identify the document components for classification. The extracted objects are then classified according to their object type. Each of classified objects are then resized using a resizing technique having been pre-selected for the object type based on their respective abilities to resize certain types of document content over other resizing techniques. The present method advantageously extends smart or content-based scaling and is especially useful for N-up or variable-information printing. The present method finds its intended uses in enhancing N-up and handout options currently provided in a variety of print-drivers.
摘要:
What is disclosed is a system and method for performing a background deletion that exploits both local and global context to remove background and other white space between objects with the aim of retaining structural relationships between objects in the document. A document image is received and seams are carved through the image. Seams composed of uniform background pixels are identified. Adjacent seams containing background pixels are collected into groups of seams. The background seam groups are classified according to their widths. A target number of seams to be removed for each background seam group is then determined based on the classification. Seam groups which are wider will have at least the same or a greater target number of seams to be deleted therefrom than will seam groups of narrower widths. The document image is then resized by deleting seams from the seam groups based on the assigned target number.
摘要:
A system resizes content within a document that includes a document segmenter that receives a document that contains content. The document segmenter analyzes the content within the document and segments the content into a plurality of object types. An object priority applicator determines a class value associated with each object type. A location scaler identifies a datum point for each object type within the document, wherein each datum point maintains a relative location to one another regardless of document resizing. An object sizing component resizes each object based at least in part upon the class value.
摘要:
What is disclosed is a system and method for performing a background deletion that exploits both local and global context to remove background and other white space between objects with the aim of retaining structural relationships between objects in the document. A document image is received and seams are carved through the image. Seams composed of uniform background pixels are identified. Adjacent seams containing background pixels are collected into groups of seams. The background seam groups are classified according to their widths. A target number of seams to be removed for each background seam group is then determined based on the classification. Seam groups which are wider will have at least the same or a greater target number of seams to be deleted therefrom than will seam groups of narrower widths. The document image is then resized by deleting seams from the seam groups based on the assigned target number.
摘要:
A system and method for resizing a digitally represented color image are presented. A color image with pixels defined by luminance and at least one chrominance value is received. For each pixel of the color image, a luminance spatial variation and respective chrominance spatial variations in the respective neighborhood of the each pixel are computed. The luminance spatial variation and the respective chrominance spatial variations are combined to produce a respective importance value for each pixel. Selected pixels are identified based upon their respective importance values and are removed by seam carving of the color image. The seam carving identifies seams of pixels based upon the respective importance values of pixels within the seams of pixels to create a resized color image. The resized color image is produced to an image output device.
摘要:
What is disclosed is a novel system and method for content-aware resizing of a digital image. To take advantage of the characteristics of various importance maps generated for the image using different operators such as, for example, gradient, entropy, probabilistic operators, and the like, a method is provided herein for combining generated pixel importance maps. The present method uses a weighted combination of pixel importance maps—one corresponding to each image operator, to produce a hybrid map for all the image. The image can then be resized based on this hybrid map. The present method provides a high degree of image resizing flexibility and has broad applicability across differing classes of images and applications such as display, printing, packaging, and other document image processing software performing document layout, image personalization, and the like.
摘要:
A system and method for resizing a digitally represented color image are presented. A color image with pixels defined by luminance and at least one chrominance value is received. For each pixel of the color image, a luminance spatial variation and respective chrominance spatial variations in the respective neighborhood of the each pixel are computed. The luminance spatial variation and the respective chrominance spatial variations are combined to produce a respective importance value for each pixel. Selected pixels are identified based upon their respective importance values and are removed by seam carving of the color image. The seam carving identifies seams of pixels based upon the respective importance values of pixels within the seams of pixels to create a resized color image. The resized color image is produced to an image output device.
摘要:
What is disclosed is a novel system and method for content-aware resizing of a digital image. To take advantage of the characteristics of various importance maps generated for the image using different operators such as, for example, gradient, entropy, probabilistic operators, and the like, a method is provided herein for combining generated pixel importance maps. The present method uses a weighted combination of pixel importance maps—one corresponding to each image operator, to produce a hybrid map for all the image. The image can then be resized based on this hybrid map. The present method provides a high degree of image resizing flexibility and has broad applicability across differing classes of images and applications such as display, printing, packaging, and other document image processing software performing document layout, image personalization, and the like.