JPH1021020A - Pdl data processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the throughput by excluding an unnecessary PDL(page description language) data part from objects of visualization processing when objects that PDL data represent are visualized by analyzing (interpreting) the PDL data. SOLUTION: The PDL data processor performs preprocessing for deleting PDL data of objects hidden behind overlapping objects when visualizing the PDL data for print output, etc., and the load of the visualization processing is reduced. A coordinate value converting means 3 converts the coordinate values of objects that the PDL data contains into coordinate values on a single coordinate system and an inclusion analyzing means 4 analyzes the inclusion relation among the objects according to the sizes and positions of the objects to specify an object hidden owing to an overlap. A deleting means 5 deletes the PDL data of the specified object to exclude the PDL data regarding the invisible object from the PDL data as objects of the visualization processing.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to an input PDL.
Analyze (interpret) the data and PD
When visualizing the object represented by L data,
The present invention relates to a PDL data processing device that improves processing efficiency by excluding unnecessary PDL data portions from targets of visualization processing.

[0002]

2. Description of the Related Art In an image processing system using a page description language (PDL), PDL data in which graphics, text, raster images, and the like are described as objects are analyzed and visualized. Output a raster image. Conventionally, in PDL data visualization processing, PDL data analysis processing is performed,
All objects were visualized according to the order described in the PDL data.

[0003] Here, among the objects included in the PDL data, there are cases where invisible objects or partially invisible objects exist because they are covered by overlapping between the objects when they are visualized. Visualizing PDL data on such invisible objects and object parts is not necessary in principle, and wastes CPU power required for the visualization processing. In particular, since a high-resolution raster image has a huge data size, a P image including a partially invisible raster image is used.
It can be said that the CPU power wasted in DL data is also large. Also, visualization processing of complicated graphics data requires a large amount of CPU power, so that processing of an invisible graphics object is a waste of CPU power.

[0004] For the unnecessary visualization processing as described above,
Japanese Patent Application Laid-Open No. 6-119456 discloses an input PDL.
There is disclosed an image output system in which the rendering order of all the objects included in the data is designated so as not to perform the expansion processing of the region where the objects overlap. In this image output system, the order in which the objects are developed is specified, and the development processing is performed in accordance with the specified order, thereby avoiding duplication of the development processing.

[0005]

However, in the above-described image output system, since the order in which the objects included in the PDL data are expanded is specified by the user, all of the objects included in the PDL data are included. In reality, it is difficult for the user to specify the order in which the objects are developed at the time of printing. The present invention has been made in view of the above-described conventional circumstances, and automatically determines the inclusion relation between objects to eliminate PDL data relating to invisible objects, thereby reducing the load on the visualization processing of PDL data. It is an object of the present invention to provide a PDL data processing device that performs the following.

[0006]

In the PDL data processing apparatus according to the present invention, the pre-processing for deleting the PDL data of an object obscured by the overlap between the objects is performed for printing out the input PDL data. By performing the visualization, the load on the visualization process is reduced. That is, the coordinate value converting means converts the coordinate values of a plurality of objects included in the input PDL data into coordinate values on a single coordinate system, and determines the inclusion relationship between the objects based on the drawing size and position. The inclusion analysis means analyzes and specifies an object obscured by the overlap between the objects. Then, for this specified object, its PDL
The deletion means deletes the data and the P
PDL data relating to an invisible object is excluded from the DL data.

Further, in the PDL data processing device according to the present invention, for an object which is partially obstructed by the overlap between objects, a pre-process for excluding PDL data of an invisible portion from a target of the visualization process is input. By performing the PDL data visualization for print output or the like, the load on the visualization processing is reduced. That is, the coordinate value converting means converts the coordinate values of a plurality of objects included in the input PDL data into coordinate values on a single coordinate system, and determines the inclusion relationship between the objects based on the drawing size and position. The inclusion analysis means analyzes and specifies an invisible portion of the object that is covered by a partial overlap between the objects and a visible portion where such overlap does not occur. And
The dividing means divides the object into the specified invisible part and the visible part, and the rearranging means rearranges the visible part of the object to the coordinate values on the coordinate system before the coordinate values are converted, thereby visualizing the object. The PDL data related to the invisible part of the object is excluded from the PDL data to be processed.

In the PDL data processing apparatus according to the present invention, the PDL data for the invisible object and the object part is deleted, and the visualization processing is performed from the PDL data to be visualized for print output or the like. Is performed, PDL data that has no meaning is excluded. PDL converted by performing such processing
Since the data does not include an invisible object, the CPU load used for visualizing the invisible object at the time of print processing or the like can be reduced.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment according to the PDL data processing apparatus of the present invention will be described with reference to the drawings. FIG. 1 shows the first
1 illustrates a configuration of a PDL data processing device according to an embodiment. This PDL data processing device deletes PDL data of an object that is obscured by overlapping between objects.
DL data input means 1, description analysis means 2 for analyzing PDL data, coordinate value conversion means 3 for converting coordinate values of a plurality of objects included in the PDL data into coordinate values on a single coordinate system, Inclusion analysis means 4 for analyzing the inclusion relation between objects included in the PDL data; deletion means 5 for deleting the description of the invisible object specified by the analysis of the inclusion relation from the PDL data; PDL data generating means 6 for regenerating PDL data based on remaining data (that is, visible object data).

In this example, the PDL data is analyzed by the description analyzing means 2 by performing parsing, lexical analysis and token extraction, and generating an instruction token sequence. In the conversion process by the coordinate value converting means 3, the description of each object is separated from the token string extracted by the description analyzing means 2 to calculate the size and the existence coordinate value of the object. That is, each object is converted from the coordinate system in which the object is described to the unified coordinate system in the page, and the converted coordinates and size data are stored in the object table 7 for each object.

In addition, the inclusion analyzing means 4 calculates the size and coordinate position of the object calculated by the coordinate value converting means 3,
Analyze containment relationships between objects. The inclusion analysis means 4 has a circumscribed rectangle table 8 and an inclusion relation table 9, calculates circumscribed rectangle data of each object, stores the data in the circumscribed rectangle table 8, and extracts an invisible object from the comparison of these circumscribed rectangles. Identify and store the data for the identification in the inclusion relation table 9. In addition, the deletion unit 5 deletes the description of the invisible object from the input PDL data based on the analysis result by the inclusion analysis unit 4, and the PDL data generation unit 6 generates PDL data to be visualized by this data. Do it again.

FIG. 2 shows a P according to a second embodiment of the present invention.
1 shows a configuration of a DL data processing device. This PDL data processing device performs a PD on an invisible part of an object that is covered by a partial overlap between objects.
L data is deleted. Instead of the deleting means 5 shown in the first embodiment, a dividing means 10 for dividing an object into an invisible part and a visible part, and a visible value part of the object by a coordinate value converting means And relocation means 11 for relocating the coordinate values to the original coordinate values on the original coordinate system before conversion. In addition, PDL data input means 1, description analysis means 2, coordinate value conversion means 3, inclusion analysis means 4, P
The DL data generation means 6 is the same as that of the first embodiment, but the inclusion analysis means 4 of this embodiment specifies an invisible part of an object that is covered by partial overlap between objects.

In the division processing by the division means 10, if there is a partially invisible raster object based on the analysis result by the inclusion analysis means 4, it is divided into a plurality of raster objects by using a rectangle circumscribing the inclusion boundary. The rearrangement unit 11 rearranges the object divided by the division unit 10 to coordinates equivalent to the object before division on the unified coordinates. Then, for the invisible part and the visible part of the divided object, the rearrangement unit 11 stores the arrangement coordinate values and the sizes of these parts in the division table 12. That is, the description of the invisible part of the object is excluded from the input PDL data, and the PDL data generating means 6 regenerates the PDL data to be visualized.

FIG. 3 shows a P according to a third embodiment of the present invention.
1 shows a configuration of a DL data processing device. This PDL data processing device deletes PDL data of objects that are covered by overlap between objects and invisible portions of the objects.
This embodiment has a configuration in which the embodiment and the second embodiment are combined.
In addition, the inclusion analysis unit 4 of the present embodiment specifies the objects that are obscured by the overlap between the objects and the invisible parts of the objects that are obscured by the partial overlap between the objects, Target for relocation processing.

Next, the processing performed by the coordinate value conversion means 3, the inclusion analysis means 4, the division means 10, and the rearrangement means 11 will be described in detail. FIG. 4 shows a procedure of a process performed by the coordinate value converting means 3. First, an output coordinate system of an object image generated by visualizing PDL data in the pre-processing is set (step S).
1) The instruction token is fetched from the current pointer of the instruction token string generated by the description analysis unit 2 to update the current pointer (step S2). Next, it is determined whether or not the fetched instruction token is NULL (step S3), and NU indicating that the coordinate value conversion process has been completed for all objects in the PDL data.
If it is LL, the process proceeds to the inclusion analysis process by the inclusion analysis means 4, while if it is not NULL, a new entry is added to the object table 7 to perform the coordinate value conversion process (step S4).

The object table 7 contains data obtained by converting the drawing coordinates and size of the object into the output coordinate system set in step S1, and the drawing coordinates and size of all the objects included in the PDL data are unified. It is stored in each entry as data on the system for each object. That is, two-dimensional coordinate conversion is performed from the original coordinate system of the object to the output coordinate system set in step S1 (step S5), and this coordinate conversion value is stored in the current entry of the object table 7 (step S6). Therefore, one entry of the object table 7 includes the transformed coordinate value of the operator unit.

Here, a set of coordinate values (x,
It is known that y) can be converted to a set of coordinate values (x ′, y ′) on another coordinate system using a 3 × 3 conversion matrix shown in (Equation 1). I have. In particular,
From the parameters a, b, c, d, tx, and ty designated by the coordinate conversion operator in the PDL data, the coordinates are calculated for each operator using the coordinate conversion formula shown in (Expression 2).

[0018]

(Equation 1)

[0019]

(Equation 2)

Then, the instruction token is fetched from the current pointer of the instruction token string generated by the description analysis means 2 to update the current pointer (step S7), and it is determined whether or not the instruction token is a description of an object (step S7). S8). As a result, when the description is an object description, the process returns to step S5 to perform the coordinate conversion process. When the description is not an object description, the object entry is described in the current entry of the object table 7 to update the table 7. Processing is performed (step S9). Then, it is determined whether or not the operator fetched in step S7 is a description of a new object (step S10). If the operator is a description of a new object, the process proceeds to step S4 to perform coordinate conversion processing. If not, the process proceeds to step S2 to fetch the next operator.

Next, FIG. 5 shows a procedure of processing performed by the inclusion analyzing means 4. First, the object indicated by the current pointer is fetched from the object table 7 generated by the coordinate value conversion means 3 and the current pointer is updated (step S21). Next, it is determined whether or not the fetched object is NULL (step S22), and NULL indicating that the circumscribed rectangle calculation process has been completed for all objects in the PDL data.
If it is, the process proceeds to step S25 described later, while if it is not NULL, the process proceeds to calculate a circumscribed rectangle of the object (step S23). Incidentally, in the calculation of the circumscribed rectangle, X,
The circumscribed rectangle when an object is placed on a coordinate plane where the Y axis is positive in the right direction and in the upward direction is (X minimum value, Y maximum value), (X maximum value, Y Is the diagonal of which is the minimum value.

The circumscribed rectangle calculated as described above is recorded in the circumscribed rectangle table 8 and the table is updated (step S24). When the object fetched by the judgment in step S22 becomes NULL, the table 8 is updated. The process proceeds to a process of analyzing the inclusion relationship between the objects (circumscribed rectangles) held in (step S25). That is, the circumscribed rectangle indicated by the current pointer is fetched from the circumscribed rectangle table 8 to update the current pointer (step S25), and the fetched circumscribed rectangle is NULL.
It is determined whether or not (step S26). As a result, if it is NULL indicating that the analysis of the inclusion relation has been completed for all the entries of the circumscribed rectangle table 8, the processing shifts to the deletion processing by the deletion means 5; (Step S2)
7).

That is, it is determined whether or not the circumscribed rectangle fetched in step S25 does not intersect with the circumscribed rectangle of another object by searching the circumscribed rectangle table 8 (step S27). If not, the flow returns to step S25. To fetch the next circumscribed rectangle. On the other hand, if they intersect, the object overlap type is determined (step S
28) If the object type is an overlap of the raster on the raster, the raster object and the inclusion area of the raster object are determined (step S29). In other cases, the inclusion relation of the circumscribed rectangle of the two overlapping objects is determined. A determination is made (step S30).

In the determination of the inclusion area between the raster objects (step S29), as shown in FIG. 6, the circumscribed rectangles of the raster object A and the circumscribed rectangle of the raster object B overlapping the instep are overlapped with each other. Is extracted. Then, the area C included in the instep A is stored in the inclusion relation table 9 as a deletion area (step S31). In the inclusion relationship determination of the circumscribed rectangle of the two overlapping objects (step S30), as shown in FIG. 7, the X and Y axes of the object A and the circumscribed rectangle of the object B overlapping the instep with respect to the origin are determined. On the coordinate planes that are positive to the right and upward, respectively, the minimum value of your X> the minimum value of your X, and the maximum value of your Y <the maximum value of your Y, and your X Maximum value of <
If the maximum value of X of Party A and the minimum value of Y of Party B> the minimum value of Y of Party A, it is determined that Party A includes Party B. Then, the result of determining the inclusive relationship between Party A and Party B is stored in the inclusive relationship table 9.
(Step S31).

The deleting means 5 deletes the included PDL data from the input PDL data for the included objects (that is, invisible objects) recorded in the inclusion relation table 9 generated by the inclusion analyzing means 4. . Therefore, in the first embodiment shown in FIG. 1, PDL data is generated by the PDL data generation means 6 based on the data subjected to the deletion processing. In the third embodiment shown in FIG. The PDL data is generated by the PDL data generation means 6 based on the data subjected to the rearrangement processing.

Next, FIG. 8 shows a procedure of processing performed by the dividing means 10. In this division processing, a raster included in two overlapping raster objects is divided into a plurality of rectangular areas, and an invisible area recorded in the inclusion relation table 9 is deleted. First, the entry of the inclusion relation table 9 is fetched to update the current pointer (step S41), and it is determined whether or not the entry is NULL (step S42). As a result, if it is NULL indicating that the division processing for all entries in the table 9 has been completed, the processing shifts to the relocation processing by the relocation means 11, while if it is not NULL, the division processing is performed (step S43). ).

That is, it is determined whether or not the entry fetched in step S41 is not the deleted area of the raster (step S43). If not, the process returns to step S41 to determine the next entry. on the other hand,
If it is the deletion area, the raster object corresponding to the deletion area fetched in step S41 is divided into a plurality of rectangular areas including the deletion area, and the deletion area (invisible portion)
Are recorded in the division table 12 (step S44). For example, as shown in FIG. 9, when the object B partially includes the object A, the area A 3 in the figure is deleted from the inclusion relation table 9 from the result of the analysis by the inclusion analysis means. The area is recorded. In the division process, the object insteps A1, A2, and A3
And the division table 10 records only two rectangular areas (visible portions) A1 and A2 excluding the deletion area A3.

Next, the rearrangement means 11 includes the dividing means 10
The coordinate arrangement of the remaining raster object area is calculated based on the division table 12 generated in step (1). For example, as shown in FIG. 10, when a divided raster object is divided into four object areas A1, A2, A3, and A4 at division boundaries L1 and L2, the starting coordinates of this object are (x1, y1). , Size is ax, Y in X direction
The direction is ay, and the coordinates of the division boundaries L1 and L2 are positions shifted by dx and dy from the start coordinates. At this time, assuming that the positive direction of the coordinate axis is right and down with respect to X and Y, the start coordinates of the divided area A1 are (x1, y) like the object.
1), and the sizes are dx and dy in the X and Y directions, respectively. The start coordinates of the divided area A2 are (x1 + dx, y
1) and the sizes are ax-dx and d in the X and Y directions, respectively.
y. The start coordinates of the divided area A3 are (x1, y
1 + dy), and the sizes are dx and a in the X and Y directions, respectively.
y-dy. The start coordinates of the divided area A4 are (x
1 + dx, y1 + dy), and the sizes are ax-dx and ay-dy in the X and Y directions, respectively.

The rearrangement means 11 recalculates the arrangement coordinates and size of the object area as described above, and records the result in the division table 12. Finally, for the PDL data input from the input means 1, the object table 7 generated by the coordinate value conversion means 3, the inclusion relation table 9 generated by the inclusion analysis means 4,
And converting the coordinates of all the objects included in the PDL data, deleting invisible objects, and dividing and deleting partially invisible raster object portions based on the division table 12 generated by the The PDL data generating means 6 generates PDL data rearranged on the original coordinates of the PDL data.

[0030]

As described above, the PD according to the present invention is
According to the L data processing device, the PDL converted in the preprocessing
Since the data does not include a description of the invisible object,
When performing the visualization processing in print output or the like, the invisible object is not visualized, and the load on the CPU can be reduced by eliminating unnecessary processing. Therefore, since the time required for the PDL data visualization processing can be reduced, high-speed printing can be performed by incorporating the PDL data processing apparatus of the present invention into, for example, a PDL printer or print server, and PDL data can be incorporated into a PDL previewer. Data preview can be speeded up.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a PDL data processing device according to a first embodiment of the present invention.

FIG. 2 is a configuration diagram of a PDL data processing device according to a second embodiment of the present invention.

FIG. 3 is a configuration diagram of a PDL data processing device according to a third embodiment of the present invention.

FIG. 4 is a flowchart illustrating an example of a procedure of a coordinate conversion process according to the present invention.

FIG. 5 is a flowchart illustrating an example of a procedure of an inclusion analysis process according to the present invention.

FIG. 6 is a conceptual diagram showing an example of an inclusion analysis according to the present invention.

FIG. 7 is a conceptual diagram showing another example of the inclusion analysis according to the present invention.

FIG. 8 is a flowchart illustrating an example of a procedure of a division process according to the present invention.

FIG. 9 is a conceptual diagram showing an example of area division according to the present invention.

FIG. 10 is a conceptual diagram showing an example of area rearrangement according to the present invention.

[Explanation of symbols]

2 ... description analysis means 3 ... coordinate value conversion means 4
... Inclusive analysis means, 5 ... Delete means, 7 ... Object table, 8 ... Bounding rectangle table, 9
... Inclusive relation table, 10 ... Division means, 11
... Relocation means,

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Ichiro Yamashita 430 Nakaicho, Ashigarakami-gun, Kanagawa Prefecture Green Tech Nakai Inside Fuji Xerox Co., Ltd.

Claims (3)

[Claims] 1. A PDL data processing device for performing pre-processing when visualizing input PDL data, wherein coordinate values of a plurality of objects included in the input PDL data are converted into coordinate values on a single coordinate system. Coordinate value conversion means, inclusion analysis means for analyzing the inclusion relationship between the objects based on the drawing size and position of the objects, and PDL for the objects obscured by the overlap between the objects specified by the inclusion analysis
A PDL data processing device, comprising: a deletion unit that deletes data. 2. A PDL data processing device for performing pre-processing when visualizing input PDL data, wherein coordinate values of a plurality of objects included in the input PDL data are converted into coordinate values on a single coordinate system. Coordinate value conversion means, inclusion analysis means for analyzing the inclusion relationship between the objects based on the drawing size and position of the objects, invisible parts and visible parts obscured by the overlap between the objects identified by the inclusion analysis A PDL data processing device, comprising: a dividing unit that divides an object into a plurality of objects; and a rearrangement unit that rearranges a visible portion of the object to coordinate values on a coordinate system before converting the coordinate values. . 3. A PDL data processing device for performing pre-processing when visualizing input PDL data, wherein the coordinate values of a plurality of objects included in the input PDL data are converted into coordinate values on a single coordinate system. Coordinate value conversion means, inclusion analysis means for analyzing the inclusion relationship between the objects based on the drawing size and position of the objects, and PDL for the objects obscured by the overlap between the objects specified by the inclusion analysis
Deleting means for deleting data; dividing means for dividing an object partially obscured by overlap between the objects specified by the inclusion analysis into an invisible part and a visible part; and displaying the visible part of the object as the coordinates. And a rearrangement means for rearranging values to coordinate values on a coordinate system before conversion.