Abstract: Methods, systems, and apparatus, including computer program products, featuring receiving user input defining a sample of pixels from an image, the image being defined by a raster of pixels. While receiving the user input, the following actions are performed one or more times: pixels are coherently classified in the raster of pixels as being foreground or background based on the sample of pixels; and a rendering of the image is updated on a display to depict classified foreground pixels and background pixels as the sample is being defined.

Abstract: A method includes receiving a selection input to define a selection mask with respect to digital data. The selection input is used to generate the selection mask with respect to the digital data. An icon is automatically associated with the selection mask, the icon being selectable to select the selection mask.

Abstract: Methods, systems, and apparatus, including computer program products, featuring receiving user input defining a sample of pixels from an image, the image being defined by a raster of pixels. While receiving the user input, the following actions are performed one or more times: pixels are coherently classified in the raster of pixels as being foreground or background based on the sample of pixels; and a rendering of the image is updated on a display to depict classified foreground pixels and background pixels as the sample is being defined.

Abstract: Methods and apparatus, including computer program products, for performing color correction. One product can receive a digital image that includes a region depicting human skin; obtain a skin color value based on a sample; receive a skin parameter value that is a tan or a blush value; use the skin color value and the skin parameter value to determine an estimated ambient lighting condition of the image; and determine a color correction based on the estimated lighting condition and a target lighting condition. Another product can use the skin color value to determine an estimated color temperature of the image and an estimated tint shift of the image, and can determine a color correction based on the estimated lighting condition and a target lighting condition and the estimated tint shift. Another product can use the skin color value and the skin parameter value to determine an estimated camera color setting.

Abstract: A system to perform modifications, or adjustments, to a digital image includes an interface component to receive selection input that indicates a location with respect to the digital data to be modified. A detector then detects a characteristic of the digital data. A configurator configures a data modification component to modify the digital data based on the detected characteristic. As configured by the configurator, the data modification component is further configured to modify the digital data based on a horizontal displacement with respect to the indicated location and a vertical displacement with respect to the indicated location.

Abstract: Methods, systems, and apparatus, including computer program products, feature receiving an image mask where the image mask identifies a first opacity value of pixels in a raster image. The first opacity value ranges between a value representing foreground and a value representing background. Each pixel in the image has a color. A first boundary pixel is identified in the image. A second opacity value for the first boundary pixel is determined using a first local color model of opacity. The first local color model of opacity is determined based on the colors of the pixels in the image within a local neighborhood of the first boundary pixel.

Abstract: A computer implemented method includes receiving, by a computer, a plurality of objects, each object in the plurality having one or more associated attributes and an associated visual representation, wherein a sequential arrangement of the plurality of objects is specified based on the one or more associated attributes. The method includes defining a path according to a space-filling curve. The method includes determining that a visual representation of a first object in the sequential arrangement has a shape that is incompatible with a current position on the path. The method includes responsive to the determining, reordering the sequential arrangement, including assigning at least one visual representation of a second object to the current position on the path. The method includes assigning the visual representation of the first object to a subsequent position on the path with which the shape is compatible.

Abstract: Methods, systems, and apparatus, including computer program products, featuring receiving user input defining a sample of pixels from an image, the image being defined by a raster of pixels. While receiving the user input, the following actions are performed one or more times: pixels are coherently classified in the raster of pixels as being foreground or background based on the sample of pixels; and a rendering of the image is updated on a display to depict classified foreground pixels and background pixels as the sample is being defined.

Abstract: Systems, methods, and program products for subjective and locatable color theme extraction for images. Determining a color density for each of a plurality of colors in an image where each of the plurality of colors belongs to a color space, extracting one or more distinct theme colors from the plurality of colors based on qualitative parameters and the determined color densities, and mapping each extracted theme color to a color occurring in the image where the mapping is based on a color distance between the theme color and colors occurring in the image.

Abstract: A method, system, and computer-readable storage medium are disclosed for editing a digital image with automatic conversion of region modalities. Input comprising an instruction to perform an operation on a first portion of the digital image may be received. The first portion of the digital image may comprise data defined by a first region modality. The operation may be applicable to data defined by a second region modality. In response to receiving the input, the first portion of the digital image may be automatically converted from the first region modality to the second region modality. The operation may be automatically performed on the converted first portion of the digital image (i.e., as defined by the second region modality).

Abstract: Methods, systems, and apparatus, including computer program products, feature receiving an image mask where the image mask identifies a first opacity value of pixels in a raster image. The first opacity value ranges between a value representing foreground and a value representing background. Each pixel in the image has a color. A first boundary pixel is identified in the image. A second opacity value for the first boundary pixel is determined using a first local color model of opacity. The first local color model of opacity is determined based on the colors of the pixels in the image within a local neighborhood of the first boundary pixel.

Abstract: An example method includes receiving a first selection location and at least one selection parameter with respect to digital data. A portion of the digital data is selected relative to the first selection location. The selecting of the portion includes assigning an energy value to each pixel within a selection proximity of the selection location. The selection proximity is determined based on the selection parameter and the energy value being a function of distance from the selection location. The selecting of the portion further includes generating a selection value for each pixel within the selection proximity, based on the assigned energy value and on a pixel characteristic difference between the relevant pixel and at least one neighboring pixel. The selection value determines whether the relevant pixel is included in the selected portion of the digital data.

Abstract: A system to perform modifications, or adjustments, to a digital image includes an interface component to receive selection input to enable selection of the digital data to be modified. A detector then detects a characteristic of the digital data. A configurator automatically configures a function, supported by a data modification component, to modify the digital data. The automatic configuration of the function is performed using the detected characteristic of the digital data to be modified.

Abstract: Methods and apparatus, including computer program products, for receiving user selection of an ordering for a plurality of objects. Each object in the plurality having one or more associated attributes and an associated visual representation. The selected ordering specifies a sequential arrangement of the plurality of objects based on one or more values associated with each of the one or more associated attributes. The sequential arrangement is presented in a visual presentation by presenting for each object in the sequential arrangement the associated visual representation at a position on a path defined by a space filling curve and according to the sequential arrangement.

Abstract: A method, system, and computer-readable storage medium are disclosed for editing a digital image with automatic conversion of region modalities. Input comprising an instruction to perform an operation on a first portion of the digital image may be received. The first portion of the digital image may comprise data defined by a first region modality. The operation may be applicable to data defined by a second region modality. In response to receiving the input, the first portion of the digital image may be automatically converted from the first region modality to the second region modality. The operation may be automatically performed on the converted first portion of the digital image (i.e., as defined by the second region modality).

Abstract: Method and apparatus for segmenting a first region and a second region. A method for defining a boundary separating a first region and a second region of a digital image includes determining using a learning machine, based on one or more of the color arrangements, which pixels of the image satisfy criteria for classification as associated with the first region and which pixels of the image satisfy criteria for classification as associated with the second region. The digital image includes one or more color arrangements characteristic of the first region and one or more color arrangements characteristic of the second region. The method includes identifying pixels of the image that are determined not to satisfy the criteria for classification as being associated either with the first region or the second region. The method includes decontaminating the identified pixels to define a boundary between the first and second regions.

Abstract: Methods, systems and apparatus, including computer program products, for processing an image. A first tone value is determined for a location within the image based upon attributes of pixels within a first neighborhood surrounding the location. The first tone value specifies a local weight for a first tone adjustment in the image. A second tone value is determined for the location based upon attributes of pixels within a second neighborhood surrounding the location. The second tone value specifies a local weight for a second tone adjustment in the image. The image is adjusted at the location using the first and second tone adjustments according to the local weights specified by the first and second tone values, respectively.

Abstract: A method, system, and computer-readable storage medium are disclosed for editing a digital image with automatic conversion of region modalities. Input comprising an instruction to perform an operation on a first portion of the digital image may be received. The first portion of the digital image may comprise data defined by a first region modality. The operation may be applicable to data defined by a second region modality. In response to receiving the input, the first portion of the digital image may be automatically converted from the first region modality to the second region modality. The operation may be automatically performed on the converted first portion of the digital image (i.e., as defined by the second region modality).

Abstract: A user identifies an area of a digital canvas. Color gradients are determined based on a corresponding area on a reference. Brush strokes are applied in the area of the digital canvas, the brush strokes having trajectories based on the color gradients.

Abstract: Methods and apparatus, including computer program products, implementing techniques for identifying one or more objects within an image. The techniques include receiving an image that includes at least one object; identifying a plurality of edge pixels in the image, an edge pixel being a pixel that borders two contrasting areas of the image, the plurality of edge pixels including both inner edge pixels and outer edge pixels; and finding a substantially connected component correlated with each object, the substantially connected component comprising a set of the edge pixels that are connected by traversing substantially only edge pixels.