JPH09172542A - Image reader - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide images desired by a user for the various kinds of originals by setting a threshold in performing binarization by the user in the case of binarizing multi-valued data, extracting the features of original images and performing the various kinds of processings. SOLUTION: The multi-valued data of the original read by a CCD 7 or the like are binarized by a binarization processing part, based on the threshold set by a CPU 16 through a parameter setting part 30 and an original size, a blank area, a halftone area and a text area are extracted as the features of the original by an area judgement part in pre-scanning, based on the binarized data. A judgement processing at the time is performed by performing the binarization, based on the threshold set through the parameter setting part 30 by the user. In this case, a parameter set is prepared so as to match with the difference of the kind of the original and the request of the user and the user sets a desired parameter from the parameter set.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image reading apparatus for reading an original image and extracting features.

[0002]

2. Description of the Related Art As a feature of a document image, for example, a method for detecting a document size is disclosed in Japanese Patent Laid-Open No. 3-165175, and a method for detecting a halftone is Japanese Patent Laid-Open No. 61-24.
No. 8661 and Japanese Patent Laid-Open No. 62-202672.
As a method for detecting noise, Japanese Patent Laid-Open No. 62-15105
No. 3 discloses this.

[0003]

However, when the features of the original image are automatically extracted and various processing is performed, if only the fixed determination parameter is used for the determination, the image desired by the user for various originals is obtained. There is a problem that you can not get.

In view of the above-mentioned conventional problems, the present invention provides an image reading apparatus capable of obtaining an image desired by a user for various originals when various characteristics are extracted and various processings are performed. The purpose is to do.

[0005]

In order to achieve the above object, the present invention provides a document reading means for reading a document image and outputting multivalued data, and multivalued data from the document reading means with a variable threshold value. Binarizing means for binarizing, feature extracting means for extracting the characteristics of the document based on the binary data from the binarizing means, and threshold setting means for setting the threshold of the binarizing means by the user. It is characterized by having.

Further, the threshold value setting means is provided on the host side, and when the document reading means prescans the document, the characteristic of the document extracted by the feature extracting means is transferred to the host side. .

Further, the feature extracting means extracts at least two features of the document size, the white background area, the halftone area and the text area, and the threshold setting means uses the 2
It is characterized in that each threshold for extracting the above features can be set as a set.

[0008]

Embodiments of the present invention will be described below with reference to the drawings. 1 is a block diagram showing an embodiment of an image reading apparatus according to the present invention, FIG. 2 is a block diagram showing the image reading apparatus of FIG. 1, and FIG. 3 shows an operation of the image reading apparatus of FIG. 2 in a book mode. Explanatory drawing, FIG. 4 is FIG.
FIG. 5 is an explanatory view showing the operation of the image reading apparatus in the ADF mode, FIG. 5 is a block diagram showing in detail the image processing section of FIG.
6 is a flow chart for explaining the feature extraction processing of the image reading apparatus of FIG. 1, FIG. 7 is an explanatory view showing the document size detecting method of FIG. 6, and FIG. 8 is an explanation showing the white background area detecting method of FIG. FIGS. 9A and 9B are explanatory views showing the detection method of the halftone area of FIG. 6, FIG. 10 is an explanatory view showing the detection method of the text area of FIG. 6, and FIG. 11 is an explanatory view showing a matrix used for isolated point removal. .

First, the structure of the image reading apparatus will be described with reference to FIGS. In FIG. 2, the device body 1
An automatic paper feeder (ADF) 2 is installed on the upper right side of the
The apparatus main body 1 and the ADF 2 constitute an image scanner. The document 13 that is automatically fed by the ADF 2 onto the document reading table 3 (below the document pressing plate 14 in the figure) is
It is read by an exposure optical system 9 including a light source 4a, mirrors 4b, 5a, 5b, a lens 6 and a one-dimensional photoelectric conversion element (CCD) 7. A reference white plate 15 for shading correction is arranged at the end of the document reading table 3. AD
F2 has an ADF unit 10 having a stepping motor 12 and a document table 11.

This image scanner has, as an original reading mode, a book mode in which the exposure optical system 9 moves as shown in FIG. 3 and an ADF mode in which the exposure optical system 9 does not move using the ADF 2 as shown in FIG. . Light source 4a
The mirror 4b is mounted on the traveling body 4, and the mirrors 5a, 5b are mounted on the traveling body 5. The traveling bodies 4, 5 are moved in the sub-scanning direction by the stepping motor 8 in the book mode. In the ADF mode, the document 13 on the document table 11 is conveyed by the separation roller 29 and the paper feed roller 30 and read by the fixed traveling bodies 4 and 5.

In FIG. 1, the CPU 16 operates the light source driver 17 to turn on the light source 4a at the time of reading an original, and then causes the CCD 7 driven by the CCD driving section 18 to read the reference white plate 15. The data obtained by reading the reference white plate 15 is converted into digital data by an internal A / D converter (not shown) in the image processing unit 19, and is also stored in an internal RAM (not shown). Next, in the book mode, the CPU 16 drives the stepping motor 8 by the motor driver 20 to move the traveling bodies 4 and 5, and in the ADF mode, drives the stepping motor 12 by the motor driver 28 to convey the original document. Read by CCD 7.

The analog video signal a of the document photoelectrically converted by the CCD 7 is an image processing unit 19 shown in detail in FIG.
In the above, the analog video processing unit 21 performs processing up to digital conversion, the shading correction processing unit 22 performs shading correction, and the image data processing unit 23 performs various image processing, and then the parameter setting unit 30 is set. It is binarized by the binarization processing unit 24 based on the threshold value set by the CPU 16 via the above.

At the time of pre-scanning, the features of the document are extracted by the area determination unit (feature extraction unit) 31 shown in FIG. 6 based on the binarized data b. The original feature data extracted during the prescan and the original image read during the main scan are sequentially stored in the scan buffer 25 shown in FIG. 5, and the I / F controller 26 outputs this data to an external host computer. Control for. In this case, the buffer controller 27 uses the scan buffer 2
The input / output of the image data with respect to 5 is managed.

Next, the feature extraction processing will be described with reference to FIGS. In FIG. 6, first, the document size is detected (step S1). FIG. 7 shows a state in which a diagonally-lined original 13 is placed on the original reading table 3, abutted against the origin (x0, y0) of a corner, and pressed by the original pressing plate 14,
The size of the document 13 can be detected by the difference in density between the frame portion of the document 13 and the surface of the document pressing plate 14. Here, since the optical density value op is about 0.1 in general, the density of the original 13 shown by the diagonal lines is
By pre-configuring the surface of the document pressing plate 14 to have a density that allows the p value to be identified, and identifying the start position (x0, y0) to the end position (x1, y1) of the document 13 in the xy direction, the document 1
A size of 3 can be detected. The size of the original 13 can be detected by discriminating the original 13 and the original pressing plate 14 with a threshold for binarization.

When the size of the manuscript 13 is detected, the characteristics of the manuscript area are next extracted, and first, the white background area in the manuscript image is determined (steps S2 and S3). The shaded area in FIG. 8 indicates a white background area, and the blank area indicates an image having some feature.
Further, in this example, the determination area is divided into rectangular blocks and the characteristics of the blocks are determined. Therefore, even if the area other than the shaded area may include a white background portion, it is divided into blocks and the block is a white background area according to the area ratio of the white background area and the other area. It can be judged to be other than. This white background region can be detected by the threshold value when binarizing similarly.

Next, the halftone area is detected (step S).
4, S5). It is possible to detect halftones by using two thresholds. In this case, the density data of the halftone region is detected, and the density is used as the halftone block in the rectangular block by using the area ratio. Determine whether or not. FIG. 9 shows the density distribution in the main scanning direction, where the density range is “0” = white to “25.
5 ”= black, the pixels existing within the two threshold values are determined as halftone. Note that FIG. 9 shows only the density distribution in the main scanning direction for the sake of simplification of the description, but in reality, by determining the density distribution in the sub scanning direction as well,
It is divided into rectangular blocks and it is determined whether or not the block is a halftone block.

Next, the text area is detected (step S).
6, S7). FIG. 10 shows the density distribution of the image including the text area in the main scanning direction. The appearance of white and black is high frequency in the text area, and therefore it is possible to determine whether or not it is the text area by detecting the frequency of the binary data. In FIG. 6, after the document size is detected (step S1), it is not a white background area (step S1).
2) The area determined to be neither the halftone area (step S4) nor the text area (step S6) is determined to be an area in which the halftone and the text are mixed (step S).
8).

Such determination processing is performed based on the threshold value set by the user via the parameter setting unit 30.
It is performed by digitizing. In this case, a parameter set is prepared in advance so as to meet different types of originals and user's request, and the user sets desired parameters from this parameter set. Note that in FIG. 6, the original area,
Although the white background area, the halftone area, and the text area are shown to be extracted in this order, in reality, they are simultaneously extracted by dedicated hardware.

Further, such a determination process is performed by prescanning the document, and various processes are performed on the document image read by the main scan based on the determination result. It should be noted that this pre-scan is read by lowering the read density from that during the main scan. When the original area is detected by the pre-scan, only the original area of the image read by the main scan is processed as effective image data, and when the white background area is detected by the pre-scan, the effective image data of the effective image data is detected. Of these, the white background area is masked, so that unnecessary noise in the white background area can be removed.

Next, with respect to the area judged as the halftone, the dither method or the error diffusion method is used to reproduce the halftone.
Value processing is performed. At this time, by performing the smoothing process on the image data before the binarization process, it is possible to remove the edge component or the like existing in the read data, which causes the image deterioration.

Next, MTF correction is performed on the area determined as text. After that, binarization is performed, and then processing for removing isolated points in the binarized data is performed. In the isolated point removal processing, binary data is arranged using a line buffer and a shift register in a matrix of 3 × 3 pixels as shown in FIG. 11, for example, and pattern matching is performed, and a pixel of interest determined to be an isolated point is converted into white data. Convert.

Here, since it is not possible to follow when the judgment is made by using the normal area judgment parameter depending on the type of the used document, the present invention is configured so that it can be set by the user. The configuration shown in can be configured to be set from an external host computer. In this case, the image scanner shown in FIG. 1 operates according to a setting command from the host computer and sends image data according to the command. Then, at the time of prescan, the host sends the area judgment parameter as a command to the image scanner, and the image scanner judges the area by the prescan based on the value of this command and sends the judgment result to the host computer. Image processing is performed based on the result.

[0023]

As described above, according to the present invention, in the case of binarizing multivalued data to extract characteristics of a document image and performing various processes, a user sets a threshold for binarizing. Since the setting is made, it is possible to obtain the image desired by the user for various originals. Further, since the characteristic of the original document extracted based on the threshold value set by the host side is transferred to the host side, the user can know the characteristic of the original document on the host side.

Further, since the thresholds for extracting at least two or more features of the document size, the white background area, the halftone area and the text area can be set as a set, the operability in setting the thresholds can be improved. Can be easy.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an embodiment of an image reading apparatus according to the present invention.

FIG. 2 is a configuration diagram showing the image reading apparatus of FIG.

FIG. 3 is an explanatory diagram showing an operation of the image reading apparatus of FIG. 2 in a book mode.

FIG. 4 is an explanatory diagram showing an operation of the image reading apparatus of FIG. 2 in ADF mode.

5 is a block diagram showing in detail the image processing unit of FIG. 1. FIG.

6 is a flow chart for explaining a feature extraction process of the image reading apparatus of FIG.

FIG. 7 is an explanatory diagram showing the document size detection method of FIG.

8 is an explanatory diagram showing a method of detecting a white background region in FIG.

FIG. 9 is an explanatory diagram showing a method of detecting the halftone region of FIG. 6;

10 is an explanatory diagram showing a method of detecting the text area of FIG.

FIG. 11 is an explanatory diagram showing a matrix used for isolated point removal.

[Explanation of symbols]

 7 CCD 19 image processing unit 24 binarization processing unit 25 scan buffer 26 I / F controller 30 parameter setting unit 31 area determination unit (feature extraction unit)

Claims (3)

[Claims] 1. A document reading unit that reads a document image and outputs multivalued data, a binarizing unit that binarizes the multivalued data from the document reading unit with a variable threshold, and the binarizing unit. An image reading apparatus comprising: a feature extracting unit that extracts a feature of a document based on binary data from the above; and a threshold setting unit that a user sets a threshold of the binarizing unit. 2. The threshold value setting means is provided on the host side, and when the document reading means prescans a document, the feature of the document extracted by the feature extracting means is transferred to the host side. The image reading device according to claim 1. 3. The feature extracting means extracts at least two or more features of a document size, a white background area, a halftone area and a text area, and the threshold setting means extracts the two or more features. 3. The image reading apparatus according to claim 1, wherein each of the thresholds can be set as a set.