An apparatus configured to generate image data represented in achromatic color from input image data and output the generated image data to a printer includes a controller. The controller is configured to replace color information of an object included in the input image data with an achromatic signal value, determine, based on an achromatic signal value corresponding to color information of a pixel of interest in the input image data, whether the pixel of interest satisfies a predetermined condition, and perform enhancement processing on the color information of the pixel of interest in a case where the pixel of interest is determined not to satisfy the predetermined condition.

A printing apparatus includes: a head which discharges liquid to a medium; and a controller. The controller obtains print data for forming an image on the medium with a dot formed by making the liquid to land on the medium, the image including a code having information; selects, in the obtained print data, dot data corresponding to the dot forming the image as selected data, determines whether a first dot pattern including the selected dot data matches a predetermined delete pattern, and determines whether a second dot pattern including the selected dot data matches a predetermined exclusion pattern; performs a correction of the print data based on results of the determinations; and discharges the liquid from the head to the medium, based on the print data after the correction, to form the image on the medium.

A recording device includes a recording unit configured to execute recording on a recording medium using a color material of cyan, magenta, yellow, and black, and a control unit configured to control recording executed by the recording unit, wherein the control unit causes the recording unit to record an edge region of black data included in image data using at least the color material of black, causes the recording unit to record an inner region on an inner side of the edge region of the black data using at least the color material of cyan, magenta, and yellow, and sets the amount of the color material of black per unit area of the edge region to be greater than the amount of the color material of black per unit area of the inner region.

Systems and apparatuses for applying coating to nails are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, to performing image processing on an image of the nail to locate a boundary of the nail. The method can further include determining a path along which to move the nail relative to an applicator, the applicator being used to coat the nail. In a further embodiment, using the located boundary of the nail, a dispensing procedure for the applicator to follow to coat the nail is determined.

A device for removing a noise artifact from a document receives a scan of the document, where the document contains a noise artifact at least partially obstructing a portion of the document. The device generates an image of the document, and extracts a first set of features from the image. The device identifies noise artifact features from the first set of features, and generates a second set of features by removing the noise artifact features. The device generates a test clean image of the document based on the second set of features. The device determines whether a portion of the test clean image that previously displayed the noise artifact corresponds to a counterpart portion of the training clean image. If it is determined that the portion of the test clean image corresponds to the counterpart portion of the training clean image, the device outputs the test clean image.

A method to reduce background noise in a document image includes: extracting, from the document image, a connected component corresponding to a background of the document image; generating a histogram of pixel values of the connected component; generating a replacement range using a range pruning algorithm that narrows a range of the histogram by iteratively discarding at least one pixel value and corresponding pixel count of the histogram from at least one side of the histogram; selecting, from the connected component, at least one pixel having a corresponding pixel value within the replacement range; converting the corresponding pixel value of the at least one pixel to a uniform background color; and outputting, subsequent to the converting, the document image.

The image processing apparatus of the present invention includes: a generation unit configured to generate a sharpness recovery amount for recovering degradation of a spatial frequency response from a target image; and a line width correction unit configured to perform line width correction processing for the target image based on the sharpness recovery amount, and the line width correction unit corrects a line width in accordance with a sign of a pixel whose absolute value of the sharpness recovery amount is large in a case where signs of the sharpness recovery amounts reverse between adjacent pixels of the target image.

Mold lock is remediated by performing a layer-by-layer, two-dimensional analysis to identify unconstrained removal paths for any support structure or material within each two-dimensional layer, and then ensuring that aligned draw paths are present for all adjacent layers, all as more specifically described herein. Where locking conditions are identified, a sequence of modification rules are then applied, such as by breaking support structures into multiple, independently removable pieces. By addressing mold lock as a series of interrelated two-dimensional geometric problems, and reserving three-dimensional remediation strategies for more challenging, complex mold lock conditions, substantial advantages can accrue in terms of computational speed and efficiency.

A computational photography system is described herein including a guidance system and a detail enhancement system. The guidance system uses a first neural network that maps an original image provided by an image sensor to a guidance image, which represents a color-corrected and lighting-corrected version of the original image. A combination unit combines the original image and the guidance image to produce a combined image. A detail-enhancement system then uses a second neural network to map the combined image to a predicted image. The predicted image supplements the guidance provided by the first neural network by sharpening details in the original image. A training system is also described herein for training the first and second neural networks. The training system alternates in the data it feeds the second neural network, first using a guidance image as input to the second neural network, and then using a corresponding ground-truth image.

A quantized value for a pixel of interest in an input image is derived by using a predetermined threshold value matrix. Then, based on a pixel value group in a predetermined reference area including the pixel of interest in the input image and a threshold value group corresponding thereto, directionality of correction is determined. Further, based on the pixel value group and the threshold value group, whether or not the pixel of interest satisfies a predetermined condition for changing the quantized value is determined. Then, based on both the determination results, the quantized value is corrected.