The image processing apparatus includes: an abnormality detection unit configured to detect one or more abnormalities included in a target image and an abnormality exclusion processing unit configured to exclude a specific abnormality from the detected one or more abnormalities. In a case in which a detection area of a certain abnormality among the detected one or more abnormalities and a detection area of another abnormality overlap with each other and a type of the certain abnormality and a type of the another abnormality are different from each other, when brightness information of one of the certain abnormality and the another abnormality satisfies a specific condition, the abnormality exclusion processing unit excludes the one of the certain abnormality and the another abnormality from the detected one or more abnormalities.

An original image is read as an aggregate of a plurality of pixels in which adjacent pixels have different colors (R, G, and B) in a main scanning direction and in a sub-scanning direction, and the read pixels of the respective colors are stored in a line memory in association with information on relative positions of the pixels with respect to another pixel. Then, the stored pixels are sorted so that pixels having the same color are adjacent to each other, and an abnormal pixel (dust) not present in the original image is detected based on the state of the sorted pixels. With this, the dust not present in the original image is detected without increasing the cost, and the dust is corrected without forming a conspicuous trace of correction.

In one example, a document scanner has a fixed-position scan bar and a built-in translatable calibration target. The scan bar has a linear array of imaging elements aimed in an imaging direction. The calibration target is spaced apart from and parallel to the linear array, and has a planar surface orthogonal to the imaging direction spanning the length of the linear array. The target is translatable during a calibration in a direction in a plane of the surface.

According to the present disclosure, an image-processing apparatus acquires scan information of the read images read by the image-reading apparatus, generates temporal change data based on the statistical information and the scan information, determines whether the temporal change data satisfy a threshold, and outputs notice information when the temporal change data are determined as failing to satisfy the threshold.

An image forming apparatus includes an image forming unit configured to form a predetermined pattern image on a sheet, a notifying unit configured to provide a notification of an orientation for placing the sheet on which the predetermined pattern image is formed by the image forming unit, on a placement portion, a reading unit configured to read the sheet on a line to line basis, to generate image data, and a detection unit configured to detect a streak-shaped image extending in a direction along a predetermined edge of the sheet, by analyzing the image data generated by reading the sheet by the reading unit, wherein the notifying unit provides a notification of a placement orientation for allowing the sheet, on which the predetermined pattern image is formed, to be read on a line to line basis, the line extending in a direction along the predetermined edge.

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 method, an image forming apparatus, and a storage medium are provided in embodiments of the present disclosure. The image processing method includes acquiring a first color component value and a second color component value of each pixel of a to-be-processed image in a preset color space; determining a color cast pixel according to the first color component value and the second color component value of each pixel; and performing pixel correction on each color cast pixel to obtain a corrected to-be-processed image. In the technical solutions of various embodiment of the present application, the color cast pixel in the to-be-processed image is determined by the first color component value and the second color component value of the pixel, and the pixel correction is performed on the color cast pixel, which removes colored noise in the printed image and improves image printing quality.

In an image reading device, a controller is configured to perform: calculating a ratio between first and second reference data as evaluation data; designating a target light receiving element from a plurality of light receiving elements one by one sequentially; calculating average evaluation data of the target light receiving element by averaging the evaluation data of a second number of light receiving elements located at positions apart every predetermined distance equal to a length of a first number of consecutively arranged light receiving elements; setting an evaluation range of the target light receiving element by adding/subtracting a predetermined value to/from the average evaluation data; determining whether the evaluation data falls within the evaluation range; in response to determining that the evaluation data is out of the evaluation range, revising the second reference data of the target light receiving element; and generating correction data using the second reference data after revision.

As set forth herein, methods and systems for automated image defect detection. An input image is subjected to skew detection and contaminant detection. Upon detection of skew of and/or contaminants in the image data, correction data, including indicia of the contaminants/skew, correction angles and directions are calculated and displayed on an electronic representation of the document. Automatic correction may then be performed to correct the detected defects, allow the defects to remain, or re-scan the original document to generate new image data without the detected defects.

A three-dimensional object detection has an image capturing device, an image conversion unit, a three-dimensional object detection unit, a three-dimensional object assessment unit, first and second foreign matter detection units and a controller. The image capturing device captures images rearward of a vehicle. The three-dimensional object detection unit detects three-dimensional objects based on image information. The three-dimensional object assessment unit assesses whether or not a detected three-dimensional object is another vehicle. The foreign matter detection units detect whether or not foreign matter has adhered to a lens based on the change over time in luminance values for each predetermined pixel of the image capturing element and the change over time in the difference between an evaluation value and a reference value. The controller outputs control commands to the other means to suppress the assessment of foreign matter as another vehicle when foreign matter has been detected.