A document type recognition apparatus includes an image region separation unit, a smoothing unit, an edge enhancement unit, a histogram creation unit, and a document type recognition unit. The image region separation unit outputs a signal indicative of each region obtained by separating an input image into a character region and a pattern region. The smoothing unit performs smoothing processing to remove halftone dots of a particular number of lines or greater in the pattern region of the input image. The edge enhancement unit outputs an image subjected to edge enhancement processing depending on an amount of edge on an edge portion of the character region in the input image subjected to the smoothing processing. The histogram creation unit creates a histogram of the image subjected to the edge enhancement processing. The document type recognition unit recognizes a document type of the input image by utilizing the histogram.

An image reading device includes: a scanner glass; photo-sensors arranged at intervals in a main scanning direction to read a document conveyed in a sub-scanning direction; an adjuster that adjusts the size of an overlapping area between a first and second image obtained by neighboring photo-sensors, the overlapping area constituting a first area of the first image and a second area of the second image; a superimposing portion that shifts either one of images of the first and second area to the other one; a judgment portion that judges whether the images having different focal depths exist based on the degree of matching between the first and second area; and a detector that detects a foreign body on the scanner glass platen by detecting a continuous image stretching in a document conveying direction in both of the images having different focal depths, if the images having different focal depths exist.

An image processing apparatus has a storage configured to store image data representing a color image, the image data being constituted by multiple pixels, each of the multiple pixels having a gradation value, and a controller. The controller is configured to extract pixels, from among the multiple pixels, within a specific color range as target pixels, adjust the gradation values of the target pixels such that brightness values of the target pixels are lowered, generate a histogram of index values corresponding to quantities of the brightness values of the multiple pixels constituting the image data after the gradation values of the target pixels are adjusted, set a first threshold value based on the histogram as generated, and apply a binarizing process to the image data using the first threshold value.

According to exemplary methods, a selection of a paper type for producing an image is received. A database of background suppression values associated with paper types is searched. Responsive to not finding a background suppression value associated with the paper type, the database is updated for the paper type. According to the method of updating, a page of the paper type is scanned and image data obtained by scanning the page is analyzed. Background luminance for the page is determined based on analyzing the image data. A background suppression value is calculated for the page based on the background luminance. The paper type and the background suppression value for the page are added to the database. The background suppression value is associated with the paper in the database.

A three-dimensional image data generation system includes: an editing unit configured to edit grayscale image data in which a density level for specifying an foaming height of a thermally expandable sheet is set for each coordinate in a planar direction; and a conversion unit configured to, when the editing unit changes a size in the planar direction of an image region included in the grayscale image data, convert the density level in correspondence with a ratio of the image region between before and after the change.

A saturation ratio calculation unit calculates a saturation ratio of the saturation of an outer circumference of a color gamut of an input image to the saturation of an outer circumference of a color gamut of an output image. A histogram generation unit generates a histogram in which a plurality of pixels selected as pixels outside the color gamut are counted for each pair of lightness and hue. A magnification determination unit determines, within a range of not less than 1 and not more than the saturation ratio, a magnification by which the chromaticity of the input image to be subjected to the color gamut conversion is to be multiplied for each pair of lightness and hue based on the histogram.

Index-based geospatial analysis may include applying a first and second index-based analysis for a set of imagery. The set of imagery may include a location-specific index values used to form a histogram for a single index image (e.g., for a single surveyed field). This first analysis may be referred to as an acre-to-acre mapping, which may be useful for identifying differences in indices (e.g., NDVI vegetative health) of different parts of the field from a single day. A second day-to-day index-based analysis may be performed by calculating a histogram for each set of imagery from multiple days, combining the histograms, and generating a single equal-area index map. The index map can be applied to redistribute the histogram values within multiple days of data, which may provide a more useful map of variation in each individual image and changes between images.

A representative value calculator calculates a representative value which is a luminance value representing a main inspection object area from an input image. On the other hand, an image divider divides an image area of the input image, and sets a plurality of divided ranges. A factor calculator calculates a tone conversion factor for enhancing or suppressing contrast adjacent the representative value calculated by the representative value calculator for each area (each divided area) divided by the image divider. A tone converter converts the tone of each pixel of the input image based on the tone conversion factor for the range divided by the image divider, which range includes a pixel for image processing, and ranges adjacent that range. As a result, the contrast of the area for which enhancement is desired can be enhanced optimally.

A tone mapping unit applies tone mapping to a block of pixel values. In each of a plurality of iterations, one or more lines of pixel values are processed based on information relating to pixel values of at least one previous line of the block which have been processed in at least one previous iteration. The information is used to determine one or more tone mapping relationships which is/are used to map the pixel values of the current line to tone-mapped pixel values. Furthermore, the information is updated based on the pixel values of the current line and stored for use in processing pixel values of a subsequent line of pixel values of the block in a subsequent iteration.

An image processing apparatus includes a degree-of-degradation detector, a degree-of-degradation estimation unit, a correction system selector and a gradation correction unit. The degree-of-degradation detector detects a degree of degradation of an image data. The degree-of-degradation estimation unit estimates a dispersion of the degree of degradation in the image data. The correction system selector selects either a first gradation correction system or a second gradation correction system in accordance with the dispersion of the degree of degradation. The gradation correction unit performs gradation correction of the image data based on either the selected first or second gradation correction system.