Samsung Electronics Co., Ltd.

Ki-min Kang

Goo-soo Gahang

Choon-Woo Kim

Won-kyoung Cho

Hyeon-seok Seo

Terekhov Vladislav

Jeong-hwan Cho

Vladislav Terekhov

An image processing method and an image forming apparatus using the same. The method of processing includes dividing an image into a predetermined number of blocks, calculating an average of color signals of pixels existing in each of the blocks divided, classifying the blocks into color blocks and monochrome blocks using the calculated average, and determining whether the image is a color image or a monochrome image using a proportion of the color blocks. Accordingly, for a document wherein color and monochrome images are mixed, it is automatically determined whether an image is a color image or a monochrome image.

Method of processing image and image forming apparatus using the same

An image forming apparatus and an image forming method thereof are provided. An image forming apparatus according to an exemplary embodiment of the present general inventive concept comprises a decoder to decode a compressed image to convert the compressed image into image data, a pure black determining unit to determine whether the image data is pure black by using information of the converted image data, a section classifying unit to classify the image data into a text section and an image section by using a result of the pure black determination, and a color coordinate converter to perform color coordinate conversion on the image section of the classified sections. Therefore, it is possible to improve readability of black text.

Image forming apparatus and method

A printing method, and an image forming apparatus and image forming system to perform the method, the method including performing a multi-bit halftoning of a pixel of image data if the pixel is to be printed with a dark developer, performing a single-bit halftoning of the pixel if the pixel is to be printed with a light developer, and printing the halftoned image data.

Image forming method and system for performing different halftoning processes according to developer

An error diffusion processing method and apparatus quantizes an input grayscale value of a pixel (m, n) of an input image based on a determination of whether the input grayscale value belongs to one of ranges divided by a plurality of thresholds. The ranges include at least one shadow area which is darker than a median grayscale value, and the input grayscale value is quantized to a predetermined grayscale value which is brighter than the median grayscale value in a predetermined method and thereby a binary grayscale value of the pixel (m, n) is determined. The error diffusion processing method and apparatus obtains an error from the input grayscale value and the binary grayscale value of the pixel (m, n), and distributes the error to neighboring pixels of the pixel (m, n) according to a predetermined error diffusion coefficient and modifies input grayscale values of the neighboring pixels. Therefore, an undesirable shadow area appearing due to the overlapping of toner particles can be prevented, and also an image similar to the input image in grayscale level can be obtained.

Error diffusion processing method and apparatus

An image forming apparatus which provides a plurality of developers that have different densities for each color, and an image forming method thereof. The image forming method may include detecting a remaining amount of a first developer; and forming an image by expressing a gray scale of inputted data according to a multi-bit halftoning process using a second developer that is similar to the first developer in color and higher than the first developer in density if the remaining amount of the first developer is a preset value or less.

Apparatus and method of forming images

A method and apparatus are provided for compensating for the degradation of a print image due to a malfunctioning nozzle that irregularly ejects ink. A malfunctioning nozzle is detected among nozzles installed in an inkjet image forming apparatus, and image data of a print position adjacent to a compensation position printed by the malfunctioning nozzle is exchanged for image data of a print position in an interest or inspection region near the compensation position. Accordingly, degradation of print quality, such as, for example, an unintended visible white band, can be prevented and the lifetime of the printhead can be lengthened.

Method and apparatus for compensating for malfunctioning nozzle and inkjet image forming apparatus using the same

A method and apparatus for compensating for a defective nozzle in an inkjet image forming apparatus are provided, in which a defective nozzle of a nozzle unit is detected, ejecting statuses of nozzles of the nozzle unit are checked which eject ink at a compensation position on a printing medium corresponding to the defective nozzle and nozzles of the nozzle unit which eject ink at positions adjacent to the compensation position when the defective nozzle is detected, and at least three pieces of image data to be printed at the compensation position and the adjacent positions are swapped and printed according to the ejecting statuses of the nozzle. Accordingly, the image data are swapped for each other in order to be printed or divided and then printed. Thus, image quality degradation such as a visible white line can be prevented.

Method and apparatus for compensating for defective nozzle in inkjet image forming apparatus

Provided are a method and apparatus for determining error diffusion coefficients. The method includes: (a) setting N groups of error diffusion coefficients (N is a positive integer), in which each group includes a plurality of coefficients; (b) binarizing an image having one gray level value using each of the N groups of error diffusion coefficients; (c) detecting N fit values with respect to N binary-coded images using an evaluation function; (d) determining whether the fit values are detected a predetermined number of times; (e) when a detection number of the fit values does not coincide with the predetermined number of times, reproducing the N groups of error diffusion coefficients according to reproduction rates determined by the N fit values; (f) selecting optional error diffusion coefficients in the reproduced N groups of error diffusion coefficients, and substituting portions of data of selected error diffusion coefficients with each other; and (g) determining the N groups of error diffusion coefficients including the error diffusion coefficients containing substituted data as new error diffusion coefficients, and returning to step (b).

Method and apparatus for determining error diffusion coefficients

An apparatus and method for selectively increasing contrasts of bright and dark regions and automatically determining an appropriate degree of correction such that the image has a corrected luminance that is closer to an estimated optimal average luminance (EOAL) determined from a quantity of light at pickup. The apparatus for correcting the image comprises a real average luminance calculating means for calculating a Real Average Luminance (RAL) of an incoming image from a luminance histogram representing a luminance distribution of pixels of the incoming image, an optimal average luminance estimating means for obtaining a quantity of light using information with respect to a pickup condition of the incoming image and for estimating the EOAL from the quantity of light, and a luminance correcting means for correcting a luminance of pixels of the incoming image based on a luminance difference (&#x394;L) between the RAL and the EOAL.

Apparatus correcting image by luminance histogram

An error diffusion processing method includes determining a binary value of an input pixel according to a grayscale level of the input pixel, searching a nearest pixel that has the same binary value as the input pixel, and comparing a measured actual distance with an ideal distance between the two pixels, so as to compute a first adjustment value. By applying a noise array to an input image, a second adjustment value is also computed according to a noise value of the input pixel. Based on the first and second adjustment values, a threshold is adjusted to determine the binary value of the input pixel. The adjusted threshold is compared with the grayscale level of the input pixel, and according to the comparison result, the binary value of the input pixel is determined. By diffusing an error value, which is a difference between the grayscale level and the determined binary value of the input pixel, to neighboring pixels, the grayscale level of the neighboring pixels is changed. A third adjustment value is also applied to reduce a diagonal pattern due to binarization of the input pixel, while encouraging a perpendicular pattern.

Error diffusion processing method

An image brightness level conversion method and apparatus which converts a multi-valued brightness level of an input pixel to a bi-valued brightness level using a threshold value. If the input pixel is determined to belong to an edge area, a predetermined reasonable distance by which dots should be isolated is reduced by a noise component and the threshold value is produced using the reduced distance. If the input pixel is determined not to belong to the edge area, the threshold value is produced without using the noise component. The method provides a uniform distribution of dots on the 2-dimensional space, a decrease in a generation of a void region where no dots appear around the edge area, a reduction of unpleasant appearing fixed patterns between dots, and a decrease in the generation of a typical pattern in which dots with a same color are diagonally arrayed.

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Seongnam-si, South Korea

Ki-min Kang