JPH07193709A - Method and device for evaluating picture - Google Patents

Abstract

PURPOSE:To provide a picture evaluating device capable of quickly and stably evaluating resolution. CONSTITUTION:The picture data of a printed picture are inputted (S140) and projected data on a position including a picture pattern in a specified area out of the inputted picture data are found out (S141). The maximum and minimum values of plural data adjacent to the projected data in the area are successively found out (S146, S149) and differences between the maximum and minimum values are calculated (S150). The minimum value of the calculated differences is calculated (S153) and the picture data are evaluated based upon the minimum value of the differences.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image evaluation method and apparatus for evaluating the quality of an image printed on paper or the like.

[0002]

2. Description of the Related Art Conventionally, most of the evaluations of images printed by an image output device such as an ink jet printer, a laser beam printer, a copying machine and the like are conducted by human visual sensory evaluation. On the other hand, in some cases, ITV is not used in evaluations such as sampling outside the production line or performance evaluation during product development.
There is a method of evaluating the printed image by performing image processing on the image data read by using the area sensor such as the above.

[0003]

However, in the above-mentioned conventional visual evaluation, the evaluation results have individual differences, and the individual evaluation results themselves show ambiguous values. Moreover, since a microscope or the like is used as a tool for long-time measurement, eyes are overused, and the burden on the inspector is very large. Further, in the latter evaluation device using an area sensor such as ITV, if the measurement resolution is high, for example, if the measurement resolution is 25 μm, and the ITV of 512 × 512 bits is used, the measurement range is only 12.8 mm ^2. For example, when the evaluation is performed on the entire A3 size of 297 mm × 420 mm, the image acquisition must be repeated several tens to several hundreds of times and the image processing must be repeated. This is 1
It will take a considerable amount of time to complete the evaluation of one image.

The present invention has been made in view of the above-mentioned conventional example, and it is an object of the present invention to provide an image evaluation apparatus which can evaluate resolution at high speed and stably.

[0005]

In order to achieve the above object, the image evaluation apparatus of the present invention has the following configuration. That is, an image evaluation device for evaluating a printed image,
Image input means for inputting image data of a printed image; projection extraction means for obtaining projection data of a portion including an image pattern in a designated area of the image data input by the image input means; The maximum value and the minimum value in adjacent plural data of the projection data in the region are sequentially obtained, and the calculating means for calculating the difference between the maximum value and the minimum value, and the minimum value of the difference calculated by the calculating means Minimum value calculation means.

In order to achieve the above object, the image evaluation method of the present invention comprises the following steps. That is, an image evaluation method for evaluating a printed image, which includes a step of inputting image data of a printed image, and a step of inputting image data in a specified area of the input image data. A step of obtaining projection data, a step of sequentially obtaining a maximum value and a minimum value in a plurality of adjacent data of the projection data in the area, and a step of calculating a difference between the maximum value and the minimum value,
There is a step of calculating the minimum value of the calculated difference, and a step of evaluating the image data based on the minimum value of the difference.

[0007]

With the above construction, the image data of the printed image is input, the projection data of the portion including the image pattern in the designated area of the input image data is obtained, and the projection data of the projection data is obtained. The local maximum value and the local minimum value of a plurality of adjacent data are sequentially obtained, the difference between the local maximum value and the local minimum value is calculated, and the minimum value of the calculated differences is calculated.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT A preferred embodiment of the present invention will now be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing the schematic arrangement of a print evaluation apparatus according to an embodiment of the present invention.

In FIG. 1, image pickup devices 1 and 2 have a light receiving element (photoelectric conversion element) such as a one-dimensional CCD line sensor, and an inspection sheet (printed sheet) to be evaluated set on a document table. ) 9 is imaged in the main scanning direction, converted into an electric signal for each scanning, and output. The illumination unit 14 illuminates the imaging positions of the imaging devices 1 and 2. The moving mechanism 10 is a mechanism unit for relatively moving the imaging devices 1 and 2 and the inspection sheet 9 in the sub scanning direction 12 orthogonal to the main scanning direction 13. The moving mechanism 10 and the imaging devices 1 and 2
The image on the inspection paper 9 can be read as a two-dimensional image by the relative movement with the. In this way, the video signal over the entire area of the inspection sheet 9 to be evaluated, which is obtained by the cooperation of the imaging devices 1 and 2 and the moving mechanism 10, is A / D converted and then input to the image processing unit 4. This image processing unit 4
Performs image processing operations such as an image data fetching operation, a histogram operation, and a center of gravity operation in accordance with an operation command of the host computer 5.

The moving mechanism controller 6 controls the moving mechanism 10 in accordance with an operation command from the host computer 5.
The host computer 5 and the moving mechanism unit 6 are connected via lines 3 and 11, and these lines 3 and 11 are connected via contacts 11a and 11b. The host computer 5 and the image processing unit 4 are connected by a bus 15, and the host computer 5 and the image processing unit 4 are connected to each other.
The image data stored in the image memory unit (see FIG. 2) can be directly read. The host computer 5 and the moving mechanism control unit 6 are connected by the communication unit 16. The host computer 5 reads the calculation result in the image processing unit 4, converts it into a value required for evaluation, and displays the result and the stored image data on the monitor 17. Further, the host computer 5 includes an input unit 7 such as a keyboard and a pointing device (P
D) 8 is connected, and the operator can input various parameters necessary for evaluation using these.

FIG. 2 is a block diagram showing a schematic configuration of the image processing unit 4 of the present embodiment. Portions common to those in FIG. 1 are designated by the same reference numerals, and their description will be omitted.

In FIG. 2, for the image pickup devices 1 and 2, for example, a one-dimensional line sensor camera or a two-dimensional CCD camera is used. Image input units 101 and 102 input image signals from the image pickup devices 1 and 2 and convert them into digital signals, and also output digital image-corrected digital image data. The image input units 101 and 102 also generate and output various timing signals. 103-1
Each of 06 is an image memory unit for storing image data, the details of which will be described later. Reference numeral 109 denotes a CPU bus that transfers information between the host computer 5, the image input units 101 and 102, and the image memory units 103 to 106.
Reference numeral 10 denotes the image input units 101 and 102 and the image memory 103 to.
An image bus for transferring information between 106.

Next, the operation based on the above configuration will be described. <Image Input Unit> FIG. 3 is a block diagram showing the internal configuration of the image input units 101 and 102.

Here, the input video data 126 is
The video data 126, which is output as an analog electric signal from the imaging devices 1 and 2, is converted into a digital signal by the A / D converter 120. The data converted into the digital signal in this way is dark-corrected by the dark correction unit 121, and then input to the shading correction unit 122 and subjected to shading correction. Further, this shading-corrected image data is binarized by the binarization unit 123 as necessary, and is output by the output selection unit 124.
The output is selected and output as image data 128 to the image bus 110. Further, a timing signal generation unit 125 is provided to control the operation of each of the above units, and a control input / output signal 127 input / output from outside and the image bus 1 are provided.
The control signal 129 from 10 or the control signal generated by the timing signal generation unit 125 itself is selected and used as the internal operation signal.

The control signal 129 is output from the image input section 101 or 102 as an external control signal input / output 127 and a control signal 129 to the image bus 110. By thus enabling the operation by the control signal from the outside, it is possible to input the image data in synchronization with the plurality of image input units 101 and 102.

The various parts 120 described above are controlled by various timing signals 130 output from the timing signal generator 125.
~ 124 are controlled. This timing signal 130 is
Timing signal for A / D conversion, clock signal for determining image transfer cycle, synchronization signal required when using one-dimensional line sensor camera or two-dimensional camera, image input start signal from external or host computer 5 (not shown) ) And a transfer area signal for determining an image transfer position (time, time, etc.) from the synchronization signal to the image bus 110.

The various conditions necessary for generating the timing signal 130 are appropriately set in the host computer 5.
From the timing signal generator 1 through the CPU bus 109
25, and the timing signal is generated according to this condition. The various conditions required here are, for example, when a one-dimensional line sensor camera is used in the imaging device 1 or 2, the reading cycle and the image input position (the pixel position to be input from the line sensor camera) according to the number of pixels. Includes information that directs etc. The dark correction means the image pickup apparatus 1
Alternatively, the offset component included in the input signal from 2 is subtracted at the time of image input, and reference data is input in advance to obtain the subtraction amount to be dark-corrected. Shading correction refers to shading components included in an input signal from the image pickup device 1 or 2 from dark-corrected image data (pixel sensitivity unevenness in the case of a line sensor camera, illumination unevenness for imaging a printed matter). Which means the component to be added) is divided when the image is input,
Reference data is input in advance to obtain a division value for shading correction. Therefore, the image input units 1 and 2 have a mode for transferring image data to the image bus 110 and a mode for inputting data for the dark correction unit 121 and the shading correction unit 122.

Next, the operation of each of the image memories 103 to 106 will be described.

FIG. 4 is a block diagram showing the internal structure of each of the image memory units 103 to 106.

In this image memory unit, memory access to the memory unit 140 is made possible from the CPU bus 109 and the image bus 110. For this reason,
The access selection unit 141 uses the memory unit 140 as necessary.
You can switch the access mode to. When the memory unit 140 is accessed from the image bus 110 (when writing to the image memory), the timing generation unit 142
Outputs a control signal for controlling the data collection unit 143 and the address generation unit 144 according to the control signal 145 from the image bus 110 to access the memory unit 140 through the access selection unit 141. The data collection unit 143 stores the image data 146 from the image bus 110 in the memory unit 140.
A plurality of image data are collected so as to match the data bus width of, and output to the memory unit 140 through the access selection unit 141. The address generation unit 144 is the timing generation unit 1
According to the control of 42, the storage address of the memory section 140 is increased every writing.

A CPU bus interface 147 outputs control signals, data and addresses from the host computer 5 input from the CPU bus 109 to the access selection unit 141. The access selection unit 141
The control signal, data, and address output to the memory unit 140 are signals from the CPU bus interface 147, or the timing generation unit 142, the data collection unit 1
43 and the signal from the address generation unit 144 are selected.

FIG. 5 is a diagram for explaining the write timing from the image bus 110 in the image memory units 103 to 106.

Now, referring to FIG. 6, a case where an image of the printed matter 500 is input to the image pickup apparatus 1 using a one-dimensional line sensor will be described. The print object 500 to be input is input to the image memories 103 and 104 as a two-dimensional image while moving relatively to the one-dimensional line sensor in a direction (sub-scanning direction) perpendicular to the line direction. To do. 1
The number of pixel data for one line of the three-dimensional line sensor is H, 1
The number of scans of the three-dimensional line sensor is V, and the image input unit 10
When inputting image data of the image input area 501 (mesh line portion) with 1, the memory capacity of each of the image memory units 103 and 104 is M bytes, and the image data amount to be input is N (=
(H × V) bytes and 2M>N> M.

In FIG. 5, reference numeral 160 indicates a bus transfer clock, which is issued from the image input unit 101 and
It is input to the image memory units 103 and 104 through 0.
The image valid signal 161 is similarly issued from the image input unit 101, becomes low level and is output to the image bus 110 when the area 501 in FIG. 6 is valid, and the image bus data 162 is output.
Is the data to be stored in the image memory unit 103,
Notify 104. The image bus data 162 is
The image data output from the image input unit 101 is shown. Now, each pixel of the image data is represented by 8 bits, and the bit width of the data bus of the memory unit 140 is 32 bits.

Thus, the image data output by the image input unit 101 is stored in the image memory 103. At this time, the timing generation unit 142 causes the bus transfer clock 16
0, the data collection unit 14 based on the image valid signal 161.
The latch signals 163 to 166 are issued to No. 3. As a result, the data collection unit 143 is set to 3 in 4 clock cycles.
The image data of 2 bits (for 4 pixels) is latched. When the 32-bit latch is completed, the timing generation unit 142 issues a write signal 167 to the memory unit 140 through the access selection unit 141. Address generator 1
44 is a memory unit 140 through the access selection unit 141.
The memory address is issued to the memory unit 140, but when the writing to the memory unit 140 is completed, the address is prepared for the next writing.

In this way, the writing of the image data into the image memory 103 is repeated, and when the number of written bytes reaches M, the timing generation unit 142 of the image memory unit 103
An overflow signal 168 indicating that the data in the memory section 140 is full is output. Thus, the data from the 0th byte to the (M-1) th byte is stored in the image memory unit 103.

Next, the image memory unit 104 includes the image valid signal 161, the bus transfer clock 160, and the image memory unit 10.
It is judged from the overflow signal 168 issued by the No. 3 whether or not the image data of the image bus 110 is to be written, and the writing operation is started after the image memory unit 103 becomes full, for example, this time.

In the write operation to the image memory section 104, the write operation to the memory section 140 is repeated every 4 bytes as described above (first byte latch signal 169 to fourth byte).
Byte latch signal 172 and memory write signal 17
3) From the Mth byte, which is the next byte of the image data already stored in the image memory unit 103, to the (N-1) th byte, which is the end of the entire image area, are the image memory unit 1
It is stored in 04. In general, the number of bytes N to be written in the image memory unit is not always a multiple of 4, so it is conceivable that there will be an unwritten portion. The remaining data is stored in the data collection unit 143 and can be read by the host computer 5 as needed. Further, the write start memory address from the image bus, setting as to whether writing is permitted by the write valid signal, write information information, etc. are appropriately set in the host computer 5.
Controlled via the CPU bus.

By the above operation, for example, the image data obtained by reading the print image area # 1 (502) shown in FIG. 6 is stored in the image memory unit 103, and the image data of the area # 2 (503) is stored in the image memory unit 104. It The host computer 5 then uses the image memory units 103 and 10 as necessary.
By reading the image data stored in No. 4, image processing for image evaluation of the printed matter can be executed.

FIG. 7 is a diagram showing the configuration of the image bus 110 described above. The image bus 110 includes the processing units 181 to 184.
The switching unit 180 is provided between the two. The processing units 181 to 184 include the above-mentioned image input unit, image memory unit, and various arithmetic units.

The switching unit 180 is characterized in that the control signal line, the image data line and the like can be individually connected or released. As a result, FIG.
In, for example, the processing unit 181 can be directly connected to the processing unit 182 to exchange data. Further, for example, in the case of the configuration as shown in FIG. 2, when it is desired to input image data at the same timing and with the same resolution by using the two image pickup devices 1 and 2, the image memory unit 104 and the image input unit 102.
The switching unit 180 in the image bus 110 during the period separates the overflow signal and the area valid signal from the image data section and the control signal, and connects the bus transfer clock and the synchronization signal to thereby transfer the image data from the image pickup apparatus 1. The image data from the imaging device 2 can be stored in the image memory unit 104 via the image input unit 102 while being stored in the image memory unit 103 via the image input unit 101.

An example of such image reading will be described with reference to FIG. The widths of the respective line sensors of the image pickup apparatuses 1 and 2 are set to H1 and H2, the area 511 of the original image 510 is read by the image pickup apparatus 1, and the original image 510 is read by the image pickup apparatus 2.
Read the area 512 in the right half of. At this time, image bus 1
The switching unit 180 of 10 connects the image input unit 101 and the image memory unit 103, and the switching unit 180 of the image bus 110 connects the image input unit 102 and the image memory unit 104.
And connect. However, at this time, the switching unit 180 disconnects the image data signal from the overflow signal and the area valid signal of the control signal, and connects the bus transfer clock and the synchronization signal. In this way, the imaging device 1
And the images read by 2 are image input units 101,
102, and each of them is input to the image memory unit 103, for example.
And stored in the image memory unit 105.

FIGS. 9 and 10 are flowcharts describing the overall operation of the print image evaluation apparatus of this embodiment. This processing is executed by the host computer 5 according to the program stored in the host computer 5.

After activating the apparatus, first, in step S1, initialization processing is performed. When this initialization process ends, step S
2, the start-up screen is displayed on the monitor 27, and the process waits for menu selection in step S3. In this menu selection processing, it is possible to select either mode selection for selecting the measurement mode or adjustment mode, model selection, or end. If the end mode is selected here, step S20
In the end mode, the end process is performed in step S21, and then all the processes are ended in step S22.

When the mode selection is selected here, the process proceeds to step S4, and either the "measurement" mode or the "adjustment" mode can be selected. Here, the measurement mode is a mode in which the printed image is actually evaluated, and the adjustment mode is a mode in which the apparatus itself is adjusted. For example, the angle between the image capturing apparatus 1 or 2 and the moving mechanism is adjusted or the image is captured. Devices 1 and 2
It is possible to adjust the magnification of the optical system, adjust the relative positions of the plurality of image pickup devices 1 and 2, and correct the sensitivity of the image pickup devices 1 and 2.

When the operator selects this "measurement" mode using the input unit 7 or PD8, the process proceeds to step S5, and after setting the measurement mode, the evaluation item selection screen is displayed on the monitor 17 in step S6. The operator selects any one of the plurality of evaluation items. Then, in step S7, for the evaluation item selected in step S6, the measurement area, the parameters for image processing, etc. are newly set, or the already set parameters are changed, or the currently set parameters are set. Select whether to use the evaluation. When the parameter setting is selected in step S7, the process proceeds to step S8, parameters are set, and after setting all parameters, in step S19, it is selected whether or not to end this measurement mode.

On the other hand, if the execution of the evaluation item is selected in step S7, the process proceeds to step S9 to select the evaluation execution, and in step S10, the data used for evaluation is switched by switching the processing data. When the re-input is switched in step S10, the process proceeds to step S11, and an image to be evaluated is newly input and evaluated. When the memory is switched to the memory in step S10, the process proceeds to step S12, and the print image is evaluated using the image data stored in the image memory unit at this time. When the file is switched to the file in step S10, the process proceeds to step S13, and the image data of the already saved file is read and evaluated.

Thus, the evaluation process is executed in step S14, and the result (numerical data) is displayed on the monitor 17 in step S15. Next, in step S16, the evaluated numerical data is graphed and displayed. Next, in step S17, it is selected whether or not to save the currently obtained evaluation data. In the case of saving, the process proceeds to step S18,
Save the data. Then, the process proceeds to step S19 to select whether or not to end this measurement mode. When ending the measurement mode, the process returns to step S2 to display the startup screen, and the menu is selected in step S3. If the measurement mode is not ended, the process returns to step S6 again, and as described above, the evaluation item selection process is performed to select any one of the plurality of evaluation items.

When the "adjustment" mode is selected in the mode selection in step S4, the flow advances to step S23 to switch to the adjustment mode. Next, in step S24, the operator uses the PD 8 and the input unit 7 to select any one of the plurality of adjustment items in the adjustment item selection in step S24. For the adjustment item selected in this way, whether to newly set the measurement area or image processing parameter required for adjustment, change the already set parameter, or execute the evaluation using the currently set parameter Is selected (step S25). If the parameter setting is selected here, the process proceeds to step S26 to set the parameter. When all the parameter settings are completed, the process proceeds to step S19, and it is selected whether or not to end this adjustment mode. If adjustment execution is selected in step S25, the process proceeds to step S27, data necessary for the selected adjustment item is calculated, and then the process proceeds to step S19.
It is selected whether or not to end this adjustment mode. When ending the adjustment mode, the process returns to step S2 to display the start-up screen on the monitor 17 and select the menu, as described above. If the adjustment mode is not ended, the process proceeds to step S24 again, and any one of the plurality of adjustment items is selected in the adjustment item selection.

On the other hand, if "model" is selected in the menu selection in step S2, the process proceeds to step S28, and the evaluation of a plurality of different models (model 1, model 2, model 3, etc.) is switched or a new evaluation is performed. You can register the model to perform. That is, after selecting "model" in step S3 and selecting "switch" in step S28, the process proceeds to step S29, and one evaluation target model is selected from a plurality of different evaluation target models already registered. You can The evaluation model registered at this time can independently have various parameters in the measurement mode of step S5 or the adjustment mode of step S23.

If "register" is selected in step S28, the flow advances to step S30 to add or delete a new model, or change the name of a model already registered.

FIG. 11 is a flow chart describing the operation of the initialization process of step S1 of FIG.

First, in step S41, the image processing unit 4
To initialize. Specifically, the presence or absence of the mounting of the processing substrate, the amount of memory for storing image data, and the like are checked. Next, the process proceeds to step S42, and it is confirmed whether the initialization of the image processing unit 4 has ended normally or whether an abnormality has occurred. If an abnormality is detected, the process proceeds to step S48, waits for an instruction input as to whether or not to retry, and if retry is performed, the process returns to step S41 again to restart the initialization process from the beginning. If the retry is not performed in step S48, the process proceeds to step S49 to perform end processing, and all operations are ended.

When the initialization of the image processing unit 4 is normally completed in step S42, the process proceeds to step S43 to initialize the contact input / output unit. This contact input unit is the contact 1 of FIG.
1a and 11b are shown, and the input / output mode and the like at these contacts are set at the time of initialization. Then step S
Proceeding to step 44, it is confirmed whether the initialization of the contact input / output unit has been completed normally or whether an abnormality has occurred. If an abnormality is detected, the process proceeds to step S48 and waits for an instruction input as to whether or not to retry as described above.

In step S44, when the initialization of the contact input / output section is completed normally, the process proceeds to step S45, and the stage section is initialized. Specifically, after the origin of the stage (document table) driven by the moving mechanism 10 is set, this stage is moved to the initial position (home position). Next, in step S46, it is confirmed whether or not the initialization of the stage section has been normally completed or an abnormality has occurred. If an abnormality is detected, the process proceeds to step S48, but if the initialization of the stage portion is normally completed, the process proceeds to step S47, the parameters for evaluation are expanded, and the initialization process is terminated.

FIG. 12 is a flowchart describing the operation of the ending process of step S21 of FIG.

First, in step S51, the image processing section 4 is reset. Next, in step S52, the contact input / output unit is reset (input / output mode is released). Then, the process proceeds to step S53, the stage unit is reset (for example, returned to the initial position), the evaluation parameters are saved in step S54, and then all the operations are completed.

Next, the parameter setting, which is a feature of this apparatus, will be described in detail.

FIG. 13 is a diagram showing an example of a window display for setting the number of evaluation areas for evaluating the printed image and the evaluation area position.

In FIG. 13, reference numeral 200 represents a reduced image of the entire image to be evaluated, 201 is the set evaluation area, and 202 is the coordinates of the set evaluation area. It is defined by the respective start coordinates (XS, YS: coordinates of the upper left corner of the rectangular area) and end coordinates (XE, YE: coordinates of the lower right corner of the rectangular area). The operator can set the evaluation area 201, which is considered to be necessary for the evaluation, on the entire display image 200 by using the PD 8 such as a mouse by looking at the entire display image 200. When the position or size of these evaluation areas 201 is changed, the evaluation area coordinates 202 are also changed in association with it. The evaluation area coordinates 202 are
It is also possible to directly input from the input unit 7 such as a keyboard. Also, press the image input button 203 on the window
By clicking at D8, new image data can be input and the data can be displayed as a whole display image 200 on the window. When the OK button 204 on the window is clicked on the PD 8, the parameter value currently set is confirmed and the window is closed.
When the cancel button 205 is clicked on the PD 8, the window is closed without confirming the parameter value.

FIG. 14 is a diagram showing an example of a window display for setting the evaluation area in detail. In FIG. 14, 2
10 shows an example of a detailed display image of the evaluation area, 211 is a detailed setting area, and 212 is a coordinate value of the detailed setting area.

The evaluation area 201 in FIG. 13 roughly sets the evaluation position in the entire image, and cannot be said to be an accurate evaluation position. Therefore, the operator can set the detailed setting area 211 by using the PD 8 while looking at the detailed display image 210. This detailed display image 21
0 can be scrolled up, down, left and right, and you can freely change the position you want to see in detail. It is similar to the above description that when the position and size of the detailed evaluation area 211 are changed, the detailed area position coordinates 212 are changed in association with the change. Incidentally, this coordinate display is displayed by the start coordinate position and the end coordinate position as in the case of FIG. 13 described above.

The detailed area position coordinates 212 can also be directly input from the input unit 7. When the OK button 213 on the window is clicked on the PD 8, the parameter value currently set is confirmed and the window is closed. In addition, cancel button 214 PD
Clicking at 8 closes this window without confirming the parameter value. Note that 215 indicates the number of registered areas, which is "4" as shown in FIG. 13, and 216 indicates the enlarged area number ("1" here).

FIG. 15 is a diagram showing an example of a window display for setting the image processing parameters of the evaluation area.

In FIG. 15, 220 is an example of a detailed display image of the evaluation area, and 221 is an example of display of projection data of the detailed display image 220. Reference numeral 222 shows a display example of the value of the image processing parameter. In this example, the image processing parameters include an initial search width, an ideal pitch, a slice level, a barycenter calculation width, and the like. The operator displays the detailed display image 220 and the projection data 2 displayed.
21, the PD 8 can set image processing parameters such as the initial search width 223, the ideal pitch 224, the slice level, and the barycenter calculation width 225 on the projection data 221. Here, when the size or position of each image processing parameter is changed, the image processing parameter value 225 also changes in conjunction with it. The image processing parameter value 225 can also be directly input from the input unit 7.

The execution confirmation button 22 on the window
When PD 6 is clicked on the PD 8, image processing is performed on the image data of the detailed display image 220 using the currently set image processing parameters, and the barycentric position and the like resulting from the processing are displayed on the detailed display image 220. When the OK button 227 on the window is clicked on the PD 8, the parameter values currently set are confirmed and the window is closed. If the cancel button 228 is clicked on the PD 8, the window is closed without confirming the parameter value.

FIG. 16 is a diagram showing an example of a window display for setting criteria for evaluation and setting various correction parameters.

In this example, as a correction parameter, a reference point for correcting the setting position of the evaluation target is registered, or a chart reading position for correcting the stage speed unevenness is registered. , An example of registering a value for correcting the displacement of the evaluation area position due to the displacement of the setting position of the evaluation target is shown. By using such parameters, accurate measurement and evaluation can be performed even if the setting position of the evaluation target image is displaced or there is stage speed unevenness.

Reference numeral 230 is a whole display image, 231 is a reference point detection area, 232 is a speed unevenness correction area, 233.
Is the coordinate value of the reference point detection area, 234 is the coordinate value of the speed unevenness correction area, and 235 is the value of the relative distance from the reference point of each evaluation area. The operator displays the entire display image 230
While looking at the PD 8, the parameters such as the reference point detection area 231 and the speed unevenness correction area 232 can be set at an arbitrary position on the entire display image 230.
When the position and size of the reference point detection area 231 and the speed unevenness correction area 232 are changed, the reference point detection area coordinate value 233 and the speed unevenness correction area coordinate value 2 are interlocked with them.
34 also changes. In addition, the reference point detection area coordinate value 23
3. The coordinate value 234 of the speed unevenness correction area can be directly input from the input unit 7.

The image input button 23 on the window
When 6 is clicked on the PD 8, new image data is input and the data is displayed on the window as the whole display image 230. Further, when the OK button 237 on the window is clicked on the PD 8, the parameter value currently set is confirmed and this window is closed. When the cancel button 238 is clicked on the PD8, this window is closed without confirming the parameter value. Next, a series of operations for parameter setting will be described.

17 and 18 are flowcharts describing an example of the parameter setting operation in the measurement mode of step S8 of the flowchart of FIG.

When the parameter setting mode is entered, first in step S61, the random mode or the sequential mode is selected. Here, the random mode is one in which one of a plurality of parameters required for evaluation is arbitrarily selected and registered or changed. In the sequential mode, a plurality of parameters required for evaluation are set sequentially from the beginning according to the evaluation algorithm.

If the random mode is selected in step S61, the flow advances to step S62 to select an item. In this example, as parameter setting items that can be selected, measurement area outline setting (step S63), measurement area detailed setting (step S66), image processing parameter setting (step S69), and correction parameter setting (step S72).
There is. The operator can arbitrarily set the parameter setting items to be corrected or changed here.

In step S63, the general setting of the measurement area is selected, and as described above with reference to FIG. 13, the number of areas, the position and size of the area are set, and then the currently set parameters are set in step S64. If you want to register, OK
If the button 204 (FIG. 13) is selected, the set value is saved in step S65, and the process returns to step S61 again to proceed to the selection of the random mode or the sequential mode. On the other hand, in step S64, the cancel button 205 (see FIG.
If 3) is selected, the parameters are not saved and the process returns to step S61.

In step S66, the detailed setting of the measurement area is selected, the position and size of the evaluation area are set in detail as described above with reference to FIG. 14, and then the currently set parameters are registered. If yes, in step S67
If the button 213 (FIG. 14) is selected, step S68
Then, the set values are stored and the process returns to step S61. If the cancel button 214 is selected in step S67, the process returns to step S61 without saving the parameters.

After selecting the image processing parameter setting in step S69 and setting the parameters necessary for the image processing such as the calculation of the center of gravity as described above with reference to FIG.
When registering the currently set parameter, if the OK button 227 (FIG. 15) is selected in step S70, the process proceeds to step S71, the current set value is saved, and the process returns to step S61. On the other hand, when the cancel button 228 is selected in step S70, the parameters are not saved and the process returns to step S61.

When the correction parameter setting is selected in step S72 and the parameters such as the reference position and the speed correction position are set as described above with reference to FIG. 16, the currently set parameters are registered. Is step S7
If the OK button 237 (FIG. 16) is selected in step 3, the set value is saved in step S74 and the process returns to step S61.
On the other hand, if the cancel button 238 is selected, the process returns to step S61 again without saving the parameters.

If the sequential mode is selected in step S61, the process first goes to step S75 for setting the measurement area. The processing of steps S75 to S77 is basically the same as the processing of steps S63 to S65 described above, but if the cancel button 205 (FIG. 13) is selected in step S76, the parameters are not saved,
The difference is that the measurement area outline setting in step S75 is performed again. When the OK button 204 is selected in step S76, the process proceeds to step S77, the set value is saved, and the process proceeds to the next measurement area detailed setting in step S78.

Similarly, the detailed measurement area setting (S78 to S80: similar to S66 to S68) and the image processing parameter setting (S81 to S83: S69 to S71) are sequentially performed.
And the correction parameter setting (S84 to S86: S7)
2 to 74). The description of these processes is the same as that described above, and will not be repeated.

If the end is selected in step S61, the parameter setting mode is ended.

FIG. 19 is a diagram showing the relationship between the printed pattern and its projection data described with reference to FIG.

In FIG. 19, reference numeral 241 indicates a printed line pattern, and 240 indicates an area for performing projection calculation. Reference numeral 242 indicates projection data when the projection calculation is performed in the projection calculation area 240. The projection data 242 is the result obtained by adding the image data of the line pattern 241 in the projection calculation area 240 in the length direction of the printed line. As a result, the peak of the projection data appears at the position corresponding to the position of each line of the line pattern 241. By calculating the barycentric position of this peak, the position of the printed line pattern can be calculated.

FIG. 20 is a diagram showing an example in which the printed pattern is not a line pattern but a dot pattern.

Reference numeral 250 represents a printed dot pattern, 251 represents a projection calculation area, and 252 represents projection data. Also in the case of these dot patterns, as in the case of the line pattern, the peak of the projection data 252 appears at the position corresponding to the position of each dot of the dot pattern 250. By calculating the barycentric position of these peaks, the accurate position of the dot pattern 250 can be calculated.

Next, the centroid calculation will be described in detail.

FIG. 21 is a schematic diagram of the projection data which is the basis of the gravity center calculation, and FIG. 22 is a flowchart showing the gravity center calculation processing.

In FIG. 21, i indicates a position coordinate, and the projection data at that point is h (i). Now, the range in which the center of gravity calculation is performed is from i = m to i = n, and SL indicates the slice level when performing the center of gravity calculation. In FIG. 21, the data portion smaller than the slice level SL in the projection data h (i) is hatched, and the gravity center calculation is performed using the data in this portion.

A specific example of this calculation will be described with reference to the flowchart of FIG. This process is executed in step S14 of FIG. 9 described above.

First, in step S91, the coordinate value i is initialized to the leading coordinate value m for which the center of gravity is calculated. Next, in step S92, the projection data h (i) at the coordinate value i is compared with the size of the slice level SL. If the projection data h (i) is larger than the slice level SL, the process proceeds to step S96. The coordinate value i is incremented by 1.

On the other hand, in step S92, the projection data h
When (i) is smaller than the slice level SL, step S
Going to 93, the slice level SL and the projection data h (i)
The difference H is calculated. Next, in step S94, the difference H between the slice level SL and the projection data h (i) and the coordinate value i
The sum (Σ (i × H)) of the products multiplied by and is taken. Next, in step S95, the total sum (ΣH) of the differences H is obtained. Then, in step S96, the coordinate value i is incremented by 1,
In 97, it is judged whether or not the calculation within the range for obtaining the center of gravity is completed, and if it is not completed yet, step S92 is executed again.
Return to. When the calculation of the center of gravity is completed in step S97 in this way, the process proceeds to step S98, and the center of gravity coordinate value G =
Σ (i × H) / ΣH is calculated.

Next, a method of calculating the center of gravity when the pattern is repeatedly printed a plurality of times will be described with reference to FIGS. 23 and 24.

FIG. 23 is a diagram for explaining the projection data and the barycenter calculation parameters, and FIG. 24 is a flowchart showing the barycenter calculation processing when a plurality of patterns are repeatedly printed.

In FIG. 23, reference numeral 264 denotes projection data, 260 is the head pattern detection range, 261 is the slice level and centroid calculation range, 262 is the centroid calculation range, 2
63 indicates an ideal pitch.

In FIG. 24, first, step S101.
Then, the projection data 264 in the head pattern detection range 260
The maximum value (MAX) and the minimum value (MIN) of the slice level 261 are detected based on these MAX and MIN.
To decide. Next, in step S102, a point that is higher than the slice level 261 is searched for in the leading pattern detection range 260, and the point is set as P1. Next, in step S103, a point smaller than the slice level 261 is found from the point P1 within the leading pattern detection range 260, and the point is set as P2.

Next, in step S104, the MA of the projection data 264 in the section corresponding to the center-of-gravity calculation width 262 from the position returned from the point P2 by half the center-of-gravity calculation width 262
X and MIN are detected, and the MIN position is set as the point P3.
At the same time, the slice level in this section is calculated from MAX and MIN obtained here. Then step S
Proceeding to 105, the center of gravity is calculated by using the projection data 264 in the section of the center of gravity calculation width 262 around the point P3 and the slice level in this section obtained in step S104, and the coordinate value of the center of gravity is obtained. Then, in step S106, the coordinate value of the center of gravity is stored as the position of the line (pattern). Next, in step S107, the position obtained by adding the ideal pitch 263 to the position of the center of gravity obtained here is set as the next point P2. Then, in step S108, it is determined whether or not the number of detected lines exceeds the number designated in advance, and the processes of steps S104 to S108 are repeated until the number reaches the designated number. In this way, even if a plurality of printed patterns are printed repeatedly, the position of each line can be accurately obtained.

FIG. 25 is a diagram showing an example of a pattern used for evaluating an image printed in color.

In the drawing, Ma indicates equidistant lines (patterns) printed in magenta, Cy indicates equidistant lines printed in cyan, Ye indicates equidistant lines printed in yellow, B
k indicates evenly spaced lines printed in blocks, which are printed repeatedly.

FIG. 26 is a diagram showing another example of a pattern used for evaluating an image printed in color.

In the figure, Ma is a grid pattern printed in magenta, Cy is a grid pattern printed in cyan, and Ye.
Indicates a lattice pattern printed in yellow, Bk indicates a lattice pattern printed in black, and these are repeatedly printed.

By using such a printed pattern, not only the longitudinal positional relationship of each color but also the lateral positional relationship can be evaluated at the same time. Further, although these patterns are composed of lines, they may be composed of dot patterns, for example.

Next, the evaluation method using these evaluation patterns will be described in detail.

FIG. 27A shows an example of pitch measurement of a pattern printed with lines. Reference numeral 270 indicates a print pattern, and G (1) to G (10) indicate calculated barycentric positions.

FIG. 27 (b) is a graph showing the change in the difference pitch G '(i) between the barycentric positions of adjacent lines. This difference pitch G' (i) is G '(i) = G (i + 1). ) -G (i) 1 ≦ i ≦ 9.

FIG. 28 (a) is a diagram showing an example of ideal displacement measurement.

Reference numeral 280 denotes an ideal print pattern position, and its coordinate values are P (1) to P (8). Reference numeral 281 indicates the position of the pattern actually printed, and its coordinate values are P '(1) to P' (8). Here, the ideal positional deviation indicates the difference between the position P ′ (i) of the actually printed pattern and the position P (i) of the ideal printed pattern, and the ideal positional deviation amount is Z (i). Then, Z (i) = P ′ (i) −P (i) 1 ≦ i ≦ 8. FIG. 28B shows an example of a graph showing the measurement result of the ideal positional deviation.

FIG. 29 (a) is a diagram for explaining the measurement of color misregistration, and 291 shows a pattern printed in magenta,
The position coordinates are Ma (i) (i = 1 to 8). 29
Reference numeral 2 denotes a pattern printed in cyan, and its position coordinate is Cy (i). In this example, the color misregistration means the magenta position Ma (i) and the cyan position Cy.
It is a difference from (i), and when the color shift amount is D (i), it can be obtained by D (i) = Cy (i) −Ma (i) 1 ≦ i ≦ 8. An example of a graph showing the results of this example is shown in FIG.

FIG. 30A is a diagram for explaining the measurement of the phase shift.

In the figure, 300 indicates the position of an ideal print pattern, and its position coordinates are P (i), 1≤i≤1.
Set to 3. Reference numeral 301 denotes a pattern printed in magenta, and its position coordinates are Ma (i), 1 ≦ i ≦ 13.
Reference numeral 302 denotes a pattern printed in cyan, and its position coordinates are Cy (i) and 1 ≦ i ≦ 13. Here, the amount of deviation from the ideal print position is calculated for each of magenta and cyan.

Here, the shift amount Z (i) in the case of magenta
Z (i) = Ma (i) −P (i) 1 ≦ i ≦ 13, and the shift amount Z (i) in the case of cyan is Z (i) = Cy (i) −P (i) 1 ≦ i ≦ 13. FIG. 20B is a graph in which the calculation results for these two colors are simultaneously plotted. In FIG. 20B, the solid line represents the magenta shift amount, and the broken line represents the cyan shift amount. As in this example, it is possible to know the phase relationship between both magenta and cyan by obtaining and comparing the deviations from the ideal printing positions. Calculation and graphing of these numerical data are performed in step S of FIG. 9 described above.
This is executed in S15 and S15.

FIG. 31 is a diagram for explaining the measurement of the paper feed amount.

Reference numeral 310 denotes a printed pattern, the position coordinates of which are G (i) 1≤i≤9. Of the patterns printed here, G (1) to G (3) are printed by one scan of the print head of the printer. After completing this one scan, move the paper by a predetermined amount,
Next, G (4) to G (6) are printed in the second scan.
In this example, the paper feed amount between the first scan and the second scan is a distance corresponding to the difference between the position G (4) and the position G (1), and the paper feed amount of the second scan and the third scan. The amount is a distance corresponding to the difference between the position G (7) and the position G (4). Here, in order to further improve the measurement accuracy, lines (for example, G (1) and G (4), G (2) and G (5), and G (3) and G corresponding to the same position between the scans are used.
The intervals of (6)) are obtained, and the average value of them is defined as the paper feed amount. In the case of this example, the first scan and the second scan
The paper feed amount between the scans is the position G (4) and the position G.
The distance between (1), the distance between the position G (5) and the position G (2),
The distance between the position G (6) and the position G (3) is obtained,
The average value of them is used as the paper feed amount.

An example of measuring the resolution of a printed image and evaluating it will be described below. FIG. 32 shows an example of printing the resolution inspection pattern on the inspection paper 9.

In FIG. 32, reference numeral 320 denotes an inspection region (16 × 2 places) used for resolution evaluation (resolution of the output device), and an enlarged view of the print pattern of that portion is shown in FIG.
Is shown in. In this embodiment, this pattern is printed by repeating the operation of printing a straight line having a width of 1 dot, then leaving a blank for 2 dots and printing the next straight line. Left and right two columns (321,322) printed in this way
The respective patterns are evaluated in the 16 inspection regions 320, respectively. The reason why the pattern is evaluated by setting 16 inspection areas here is to detect a local defect in the printed pattern. Note that the thickness and spacing of the lines in this pattern are appropriately determined according to the resolution of the output device such as a printing device.
Therefore, the present invention is not limited to this embodiment. Further, the number, size, and position of the regions to be evaluated can be changed as necessary, and the present invention is not limited to the case of this embodiment.

FIG. 34 is a flow chart showing a process for obtaining the distribution of resolutions. This process is executed by the host computer 5.
Run on.

First, in step S110, the image in which the inspection pattern is read is loaded into the image memory unit, and in step S1.
In step 11, a projection data string P of a previously designated area (m × n) in the image data stored in this image memory unit is obtained. The relationship between this image data (original image) and the projection data is shown in FIG. Next in step S11
2, the projection data string P is obtained by adding all the projection data and then dividing this by the number of projection data (n).
The average value (ave) of is calculated. Next, in step S113, the absolute value | ave −P _j | of the difference from the average value (ave) is obtained for each projection data P _j , and these are added to the number of projection data (from j = 1 to j = n). Calculate the value (sum). Then, the process proceeds to step S114, and the added value (sum
) Is the number of image data in the first specified area (m ×
n), and in step S115 the value is used as the resolution variance (aveto) to evaluate the resolution of the image data.

FIG. 35 is a diagram for explaining the dispersion of resolution.

The sum of the differences 355 from the average of the projections 354 of the original image 350, normalized by the number of original image data, is the resolution variance. 351 indicates a printed pattern,
Reference numeral 352 indicates a blank portion which is not printed. 353
Is a diagram for explaining dispersion, and shows a projection 354 and a total sum 355 of differences between the projection 354 and an average (ave).

FIG. 35B shows the density ratio (S_q / W_q 
(%)) Is a diagram for explaining the
A continuous unblanked blank area (for example, 36 in FIG. 32).
The density projection of 0) is shown. Where S_q Is projection 35
4 shows the q-th maximum value of 4, and W_qIs the maximum value S_q Corresponds to
Dark areas of continuous blank areas where no pattern is printed.
The degree projection value is shown. Also, FIG. 35C shows the minimum density.
In the figure for explaining the values, this minimum density value is the qth number of the projection 354.
Local maximum g^l _qAnd the q-th minimum value g of the projection 354 ^s _qWhen
It is represented by the minimum value of the difference.

If the printed pattern is printed with sufficient resolution, each of the projection data should be clearly divided into the higher density and the lower density with respect to the average value (ave). On the contrary, when the pattern is not printed with sufficient resolution, there is no difference in density between the white part and the black part of the pattern, and the difference between the projection data and the average value is small. That is, since the dispersion of the resolution increases as the variation from the average value of the projection data increases, it can be considered that the pattern has been printed at a higher resolution as the dispersion value increases.

Therefore, as an actual evaluation method, in the present embodiment, first, the dispersion of the resolutions of non-defective patterns printed with sufficient resolution is obtained by the above-mentioned method, and this is stored in the host computer 5 as a reference value. . Then, the quality determination of the image data (that is, the quality determination of the resolution of the output device) is performed according to the percentage of the dispersion value of the resolution of the inspection pattern within the reference value.

Such an evaluation is performed on a total of 32 inspection areas, each consisting of 16 left and right inspection areas in FIG. 32, and the distribution of the values is recorded.

FIG. 36 is a flow chart showing the process of extracting and evaluating the density ratio associated with the resolution. This processing is also executed by the host computer 5.

First, in step S120, the image data is loaded into the image memory unit, and in step S121, the projection data string S for the predesignated area of the image data.
Ask for. Next, in step S122, a continuous blank area having an image signal whose sub-scanning position is the same as the designated image data area and no pattern is printed is set, and the projection data string W is obtained. .

In step S123, i is set to "2" and the count variable (count) is set to "0". Then, in step S below, the evaluation area (here,
Data number i is the projection data sequence S of. 2 to (n-3) to) seek all the maximum value S _q data (step S124~S125, S128, S130). Further, the number is counted and stored in a variable (count). This maximum value S _q is a projection value of the density between the line patterns.

Here, the determination of the maximum value is performed by the following method. That is, the p-th projection data S _p has two data before and after it, that is, p-2, p-1, p + 1, p + second projection data S _p-2 , S _p-1 , S _{p + 1.} , S _{p + 2,} the maximum value is obtained.

Next, in step S126, the density projection data W _i of the blank area at the same sub-scanning position as each local maximum value found here is extracted from the data string W, and the ratio (ri
tu). At this time, the i-th (ritu) is represented by the following equation.

Ritu = S _i × 100 / W _i (%) Then, proceeding to step S127, all (ritu) obtained in each inspection region are added, and this is divided by a variable (count) to obtain Average value of (ritu) in the area (ave
(ritu) is obtained (S129). This average value (ave ritu)
Is used for evaluation as the concentration ratio.

The description of this density ratio is given in FIG.
(B), where the density ratio is the original image 35.
The maximum value of the projection 354 with respect to 0 (S _q is the q-th maximum value), which the horizontal position of the maximum value of the ratio of (W _q corresponding to S _q) density projection data of the margin area 360 is the same Only the numbers are obtained and these are averaged. The maximum value of the projection data string in the inspection area represents the average of the densities between the patterns. Therefore, if the pattern is printed with sufficient resolution, there should be no scattering of toner or ink between the lines. Therefore, these maximum values S
_i is almost the same value as the blank space projection data W _{i at} the same sub-scanning position, that is, the ratio (ritu) is approximately 100% according to the above equation.
Should be close to.

On the contrary, when the pattern is not printed with sufficient resolution, the maximum value S _i is the blank space projection data W _i.
Is extremely small, the ratio (ritu) is close to 0%.

Therefore, the average value (ave rit
u), if this average value is larger than the threshold value for the quality judgment, it is judged that the print result of the image has been printed with sufficient resolution and is good, while if it is small, it is judged as defective. To do.

Such an evaluation is performed for each of the above-described left and right 16 areas, for a total of 32 areas, and the distribution of the values is recorded.

FIG. 37 is a flow chart showing the extraction of the minimum density difference and the evaluation using it, and this processing is executed by the host computer 5.

First, the image of the inspection pattern is loaded into the image memory section (S140), and the projection data string S of the predesignated area m × n of the image data is obtained (S14).
1). In step S143, various parameters are set, for example, i is set to "2" and the determination flag is turned off (that is, "0"). In step S144,
It is determined whether the value of i is smaller than (n-2: n is the number of projection data). As a result, from the second data (n
-3) data is sequentially processed (S143 to S143)
155).

First, in step S145, the state of the discrimination flag is checked, and if it is off, the flow proceeds to step S146 to determine whether the i-th projection data is a minimum value.
The determination as to whether or not this is the minimum value is performed by the following method. That is,
The p-th projection data S _p has two data before and after it, that is, p-2, p-1, p + 1, p + second projection data S _p-2 , S _p-1 , S _{p + 1} , When it is smaller than any of S _{p + 2} , this is the minimum value gs. On the other hand, if it is not the minimum value, the process proceeds to step S155.

If it is the minimum value, the process proceeds to step S147,
Store the i-th projection data in a variable (LocalMin),
The minimum value counter is incremented by 1, and the discrimination flag is turned on (that is, "1"). If the determination flag is not OFF in step S145 and the flag is not ON in step S148, i is incremented by 1 (S155) and the process of the next data is performed.

If the determination flag is ON in step S148, the flow advances to step S149 to determine whether the i-th projection data is the maximum value. The determination of this maximum value is performed by the following method. That is, the p-th projection data Sp has two data before and after it, that is, p-2, p-1, p + 1,
p + 2nd projection data S _p-2 , S _p-1 , S _{p + 1} , S
When it is larger than any of _{p + 2} , this is set as the maximum value gl. If it is not the maximum value, the process proceeds to step S155,
Move on to the next data.

If it is the maximum value in step S149, the process proceeds to step S150, and the i-th projection data is set to the variable (LocalM
ax), find the difference between the value of (LocalMax) and the value of (LocalMin), and store the difference in a variable (LmaxtoLmin). Then, in step S151, this variable (LmaxtoLmi
The value of n) is compared with a predetermined set value, and if it is less than or equal to the set value, the process proceeds to step S155, and the process of the next data is performed.

If it is larger than the set value in step S151, the process proceeds to step S152, the discrimination flag is turned off,
The maximum counter is incremented by 1. Further, in step S153, the value of (LmaxtoLmin) is compared with the value of the variable Min,
If the value of (LmaxtoLmin) is greater than or equal to the variable Min, step S
Proceed to 155 to move to the processing of the next data. On the other hand, (Lmaxto
If the value of (Lmin) is smaller than the variable Min, step S15
Go to 4 and store the value of (LmaxtoLmin) in the variable Min,
The position of the data is stored in (atnum).

The above processing is performed for the second to (n-2) th projection data, and the minimum (LmaxtoLmin) in this set area is obtained and stored in the variable Min. Finally, the process proceeds from step S144 to step S156, the variable Min is divided by the number of image data in the area (m × n), and this is used as the minimum density difference for evaluation of resolution.

FIG. 35C is a diagram for explaining this minimum density difference.

The maximum value of the projection 354 of the original image 350 (g^l _q
Is the q-th maximum value) and the minimum value (g^s _qIs the q-th local minimum)
Sequentially, and the difference between the maximum and minimum values of the same number (for example,
If g ^l _q-G^s _q). The minimum value of this difference is the minimum density difference
I am trying.

This minimum density difference is obtained by sequentially calculating the difference between the maximum value and the minimum value adjacent to each other in the projection data, and calculating the minimum value. Since the minimum value and the maximum value of the projection data correspond to the line portion and the line portion of the pattern, respectively, a small difference between them can be regarded as insufficient resolution of the print image. That is, the smaller the minimum density difference, the more the resolution is printed, and the smaller the difference, the lower the resolution is printed. Moreover, if the resolution is lowered even in a part of the inspection area, the value is reduced. That is, it is possible to detect even a local decrease in resolution.

In the present embodiment, for the actual evaluation of the printed image, a predetermined value is set in advance as the threshold value for the quality judgment, and if the value of the minimum density difference is larger than this value, the product is good, and if it is smaller, it is defective. It is evaluated and judged. If the minimum density difference is adopted, the position where the resolution is defective can be known, so that position is also recorded.

Such an evaluation is carried out for each of the left and right 16 areas, for a total of 32 inspection areas, and the distribution of the values,
By recording the occurrence location, it is possible to evaluate the resolution of the printed image and identify the defective location.

Numerical data or graph data may be displayed as shown in FIGS. 9 and 10 based on the density ratio, the minimum density difference, the resolution dispersion value, etc. described above. The device itself evaluates the quality and resolution of the image data based on each of the ratio, the minimum density difference, the resolution dispersion value, or a plurality of values, and the monitor 17
It may be displayed in.

Further, in the above-mentioned embodiment, the image data is the image data obtained by reading the original image, but the present invention is not limited to this. For example, the image data may be analog or digital data from a host or an image file. It may be image data input in a format.

The present invention may be applied to a system composed of a plurality of devices or an apparatus composed of one device. Further, it goes without saying that the present invention can also be applied to the case where it is achieved by supplying a program for implementing the present invention to a system or an apparatus.

As described above, according to this embodiment, the printed pattern is read by the sensor, the projection data of the predesignated area is obtained from the read image signal, and the projection data in the area is adjacent to the projection data. The matching minimum value and maximum value are sequentially obtained, and the resolution of the printed image is evaluated using the minimum value of the difference between the minimum value and the maximum value, so that highly accurate and high-speed image evaluation is possible.

[0140]

As described above, according to the present invention, there is an effect that the resolution can be evaluated quickly and stably.

[Brief description of drawings]

FIG. 1 is a block diagram showing an overall configuration of a print evaluation apparatus according to an embodiment of the present invention.

FIG. 2 is a block diagram illustrating a configuration of an image processing unit according to the present exemplary embodiment.

FIG. 3 is a block diagram showing a configuration of an image input unit of this embodiment.

FIG. 4 is a block diagram showing a configuration of an image memory unit of the present embodiment.

FIG. 5 is a diagram showing an example of transfer timing of image data in the image memory unit of the present embodiment.

FIG. 6 is a diagram showing an example in which a print image is divided into a plurality of areas and input to a memory.

FIG. 7 is a diagram showing a configuration of an image bus of this embodiment.

FIG. 8 is a diagram for explaining an example of reading and inputting a document image using a plurality of imaging devices.

FIG. 9 is a flowchart showing the operation of the print evaluation apparatus according to this embodiment.

FIG. 10 is a flowchart showing the operation of the print evaluation apparatus according to this embodiment.

FIG. 11 is a flowchart describing the operation of the initialization process of step S2 of FIG.

FIG. 12 is a flowchart describing the operation of the ending process of step S21 of FIG.

FIG. 13 is a diagram showing an example of a window display for setting the number of evaluation areas to be evaluated and the area positions in the apparatus of the present embodiment.

FIG. 14 is a diagram showing an example of a window display for setting the evaluation area to be evaluated in detail in the apparatus of the present embodiment.

FIG. 15 is a diagram showing an example of a window display for setting image processing parameters in the apparatus of this embodiment.

FIG. 16 is a diagram showing an example of a window display for setting correction parameters in the apparatus of the present embodiment.

FIG. 17 is a flowchart describing a parameter setting process (S8) in the measurement mode of the device of the present embodiment.

FIG. 18 is a flowchart describing a parameter setting process (S8) in the measurement mode of the device of the present embodiment.

FIG. 19 is a diagram showing a relationship between a print pattern and its projection data.

FIG. 20 is a diagram showing a relationship between a dot pattern and projection data.

FIG. 21 is a schematic diagram of projection data.

FIG. 22 is a flowchart showing a gravity center calculation process in the apparatus of this embodiment.

FIG. 23 is a diagram showing a relationship between projection data and a parameter of gravity center calculation.

FIG. 24 is a flowchart showing a centroid calculation process when there are a plurality of print patterns in the apparatus of this embodiment.

FIG. 25 is a diagram showing an example of a color print pattern.

FIG. 26 is a diagram showing another example of a color print pattern.

FIG. 27 is a diagram showing an example of pitch measurement, FIG. 27A shows an example of pitch measurement, and FIG.

28A and 28B are diagrams illustrating an ideal position shift, in which FIG. 28A shows a shift between an ideal position and an actually printed position, and FIG. 28B is a graph showing the shift amount.

29A and 29B are diagrams illustrating measurement of color misregistration, in which FIG. 29A shows color misregistration amounts of magenta and cyan, and FIG. 29B is a graph thereof.

FIG. 30 is a diagram for explaining the measurement of the phase shift, (a) is a diagram for explaining the shift amount of each color from the ideal position, and (b) is a graph for showing the shift amount.

FIG. 31 is a diagram illustrating the measurement of the paper feed amount.

FIG. 32 is a diagram showing an entire image of a pattern used for inspection of resolution and an inspection area.

FIG. 33 is an enlarged view of the inspection area shown in FIG. 32.

FIG. 34 is a flowchart showing a process of extracting resolution dispersion in the image evaluation apparatus of this embodiment.

FIG. 35 is a diagram for explaining parameters for evaluating resolution in the image evaluation apparatus of this embodiment.

FIG. 36 is a flowchart showing a process for obtaining a density ratio in the image evaluation device of this embodiment.

FIG. 37 is a flowchart showing a process for obtaining a minimum density difference in the image evaluation apparatus of this embodiment.

[Explanation of symbols]

 1, 2 Image pickup device 4 Image processing unit 5 Host computer 6 Moving mechanism control unit 7 Input unit 8 Pointing device (PD) 9 Inspection paper 10 Moving mechanism 17 Monitor 100 CPU 101, 102 Image input unit 103-106 Image memory unit 107, 108 photoelectric conversion unit 109 CPU bus 110 image bus 320 inspection area

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁶ Identification code Office reference number FI technical display location H04N 1/00 106 C

Claims (5)

[Claims] 1. An image evaluation apparatus for evaluating a printed image, comprising image input means for inputting image data of the printed image, and a designated area of the image data input by the image input means. , Projection extraction means for obtaining projection data of a portion including an image pattern, and sequentially obtain a maximum value and a minimum value in a plurality of adjacent pieces of projection data in the region, and calculate a difference between the maximum value and the minimum value. An image evaluation apparatus, comprising: a calculating unit for calculating the minimum value of the difference calculated by the calculating unit; 2. The image evaluation apparatus according to claim 1, further comprising an evaluation unit that evaluates the image data according to the minimum value of the difference. 3. The image evaluation apparatus according to claim 2, wherein the evaluation unit determines that the resolution of the image data is good when the minimum value of the difference is a predetermined value or more. 4. The evaluation means stores a threshold value for judging quality, and evaluates the product as a non-defective product when the minimum value of the difference is larger than the threshold value, and evaluates it as a defective product when not. The image evaluation device described in 1. 5. An image evaluation method for evaluating a printed image, comprising the steps of inputting image data of the printed image, and including an image pattern in a designated area of the input image data. The step of obtaining the projection data of the location, the step of sequentially obtaining the maximum value and the minimum value in the adjacent plural data of the projection data in the region, and the step of calculating the difference between the maximum value and the minimum value, and the calculated difference. And a step of evaluating the image data based on the minimum value of the difference, the image evaluation method.