Abstract: A liquid ejecting device includes: a head having a plurality of nozzles for ejecting droplets onto a printing medium; a movement unit configured to move the head relative to the printing medium in a relative movement direction; and a control unit configured to record a test pattern on the printing medium by controlling the head and the movement unit, and to perform recording by correcting control of the head and/or the movement unit based on a correction value obtained from the test pattern, wherein the test pattern includes a plurality of patches from which a plurality of candidates for the correction value for correcting a landing position at which the droplet lands on the printing medium in the relative movement direction are obtained.

Abstract: An image processing device includes a memory portion for storing an ejection amount conversion table showing a relationship between image data serving as reference and a fluid ejected from a fluid ejecting head for a predetermined number of pixels, and an ejection amount estimation unit which estimates an ejection amount of the fluid from input image data on the basis of the ejection amount conversion table stored in the memory portion.

Abstract: An image processing device includes a memory portion for storing an ejection amount conversion table showing a relationship between image data serving as reference and a fluid ejected from a fluid ejecting head for a predetermined number of pixels, and an ejection amount estimation unit which estimates an ejection amount of the fluid from input image data on the basis of the ejection amount conversion table stored in the memory portion.

Abstract: A color reduction processing apparatus and method that is simple to configure and adjust produces two-color print image data reflecting the impression of the original full-color image. Each pixel in a full-color image is converted to binarized principal and secondary color print data by principal and secondary color processors respectively using respective threshold value matrices. The threshold values of these matrices, which are calculated from a reference threshold value matrix stored in memory, can be adjusted, via adjustment values, to control the overall density of the principal and secondary colors. The adjustment values can be set in a matrix configuration unit. The binarized principal and secondary color print data can also be further corrected by correction and/or filtering operations performed by a correction processor.

Abstract: For image processing for repeatedly executing process segment sets including N (N is an integer of 3 or greater) unit process segments Lc, Lm, Ly, Lk, Llc, Llm and Ldy, unit process segments are executed by M (M is an integer of 2 or greater but less than N) processing units. The unit process segments include a first-type unit process segments Lc, Llc, Llm, and Lk for performing processing using a first processing method and a second-type unit process segment Lm, Ly and Ldy for performing processing using a second processing method that is different from the first processing method. Then, when executing process segment sets, the M unit process segments including at least one each of the first-type and the second-type unit process segments Lc, Lm are first executed on the M processing units.

Abstract: For image processes performed repeatedly using a plurality of processing units on a plurality of partial images aligned mutually adjacent to each other, specified processing is performed. This image process includes (i) a first-type process segment on first partial image data representing a partial image to generate M types (M is an integer of 2 or greater) of second partial image data; and (ii) the respectively corresponding M types of second-type process segments on the M types of second partial image data. When executing image processing, parallel processing is performed for the second-type process segment relating to the i-th (i is a positive integer) partial image and the first-type process segment relating to any of the (i+1)-th to the (i+p)-th (p is a positive integer) partial images.

Abstract: In image processing carried out by means of repeated execution of process set which includes N unit processes (where N is an integer equal to 3 or greater), prior to execution of the process groups, the N unit processes are assigned to a number M (where M is an integer equal to 2 or greater, but less than N) of processing modules for executing the unit processes. First, on the basis of execution results of unit processes included in the process group executed immediately prior, there is estimated an estimated load of unit processes of each class in the next process group. Then, on the basis of the estimated load, the N unit processes are assigned to the processing modules. During this process, a selected unit process which is one of the unit processes not yet assigned to a processing module, is assigned to one of the processing modules.

Abstract: Noise adding unit 700 reads the downloaded target JPEG image from memory and adds designated noise to that JPEG image. Reverse DCT transformation unit 710 performs reverse discrete cosine transformation on the noise-added JPEG image, and transforms it from space frequency to spatial coordinates. Binarization unit 720 binarizes the image that has been expanded to spatial coordinates. This makes it possible to achieve the same processing as half-tone processing on images that have undergone normal orthogonal transformation without putting a large burden on the CPU, etc. and with a small data volume even when transferring via a communication path.

Abstract: For image processing for repeatedly executing process segment sets including N (N is an integer of 3 or greater) unit process segments Lc, Lm, Ly, Lk, Llc, Llm and Ldy, unit process segments are executed by M (M is an integer of 2 or greater but less than N) processing units. The unit process segments include a first-type unit process segments Lc, Llc, Llm, and Lk for performing processing using a first processing method and a second-type unit process segment Lm, Ly and Ldy for performing processing using a second processing method that is different from the first processing method. Then, when executing process segment sets, the M unit process segments including at least one each of the first-type and the second-type unit process segments Lc, Lm are first executed on the M processing units.

Abstract: For image processes performed repeatedly using a plurality of processing units on a plurality of partial images aligned mutually adjacent to each other, specified processing is performed. This image process includes (i) a first-type process segment on first partial image data representing a partial image to generate M types (M is an integer of 2 or greater) of second partial image data; and (ii) the respectively corresponding M types of second-type process segments on the M types of second partial image data. When executing image processing, parallel processing is performed for the second-type process segment relating to the i-th (i is a positive integer) partial image and the first-type process segment relating to any of the (i+1)-th to the (i+p)-th (p is a positive integer) partial images.

Abstract: In image processing carried out by means of repeated execution of process set which includes N unit processes (where N is an integer equal to 3 or greater), prior to execution of the process groups, the N unit processes are assigned to a number M (where M is an integer equal to 2 or greater, but less than N) of processing modules for executing the unit processes. First, on the basis of execution results of unit processes included in the process group executed immediately prior, there is estimated an estimated load of unit processes of each class in the next process group. Then, on the basis of the estimated load, the N unit processes are assigned to the processing modules. During this process, a selected unit process which is one of the unit processes not yet assigned to a processing module, is assigned to one of the processing modules.

Abstract: Noise adding unit 700 reads the downloaded target JPEG image from memory and adds designated noise to that JPEG image. Reverse DCT transformation unit 710 performs reverse discrete cosine transformation on the noise-added JPEG image, and transforms it from space frequency to spatial coordinates. Binarization unit 720 binarizes the image that has been expanded to spatial coordinates. This makes it possible to achieve the same processing as half-tone processing on images that have undergone normal orthogonal transformation without putting a large burden on the CPU, etc. and with a small data volume even when transferring via a communication path.

Abstract: Noise adding unit 700 reads the downloaded target JPEG image from memory and adds designated noise to that JPEG image. Reverse DCT transformation unit 710 performs reverse discrete cosine transformation on the noise-added JPEG image, and transforms it from space frequency to spatial coordinates. Binarization unit 720 binarizes the image that has been expanded to spatial coordinates. This makes it possible to achieve the same processing as half-tone processing on images that have undergone normal orthogonal transformation without putting a large burden on the CPU, etc. and with a small data volume even when transferring via a communication path.

Abstract: A color reduction processing apparatus and method that is simple to configure and adjust produces two-color print image data reflecting the impression of the original full-color image. Each pixel in a full-color image is converted to binarized principal and secondary color print data by principal and secondary color processors respectively using respective threshold value matrices. The threshold values of these matrices, which are calculated from a reference threshold value matrix stored in memory, can be adjusted, via adjustment values, to control the overall density of the principal and secondary colors. The adjustment values can be set in a matrix configuration unit. The binarized principal and secondary color print data can also be further corrected by correction and/or filtering operations performed by a correction processor.