JPH10154191A - Business form identification method and device, and medium recording business form identification program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To identify the type of a business form at a high speed and with high accuracy from the business form image including no business form-only mark, etc., by deciding the type of the business form based on the error value between the feature value of a part excluding the handwriting area calculated from the handwriting area information registered previously on every business form and the model feature value. SOLUTION: A storage part 2 stores the handwriting area information 2a which shows the handwriting areas of plural types of business forms in the coordinates, etc., and the model feature value 2b with which the feature value are previously registered for plural types of business forms in regard to the direction feature and the edge feature of the part excluding the handwriting areas from a business form image. Then an image input part 1 fetches the business form, and a business form identification part 3 eliminates the background image from the fetched image to obtain only the business form image and calculates the feature value of the part excluding the handwriting areas from the business form image based on the information 2a. Then the error value is calculated between the calculated feature value and the value 2b, and the type of the business form shown in the business form image is decided based on the calculated error value.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a form identification method and apparatus, and a medium recording a form identification program.
In particular, the present invention relates to a form identification method and apparatus for identifying the type of a form on which a dedicated identification code or mark is not printed, and a medium recording a form identification program.

[0002]

2. Description of the Related Art In order to increase the efficiency of business processing for handling a large number of forms and slips, an OCR device which reads these at high speed and digitizes them is used.

In an OCR apparatus, first, format information such as a description position of a character figure to be read and a type of a character (whether it is a handwritten character or a printed character, or only a number or a kanji character, etc.) is registered in advance. Use of such information is indispensable for improving reading accuracy.

When continuously reading the same type of form,
Normally, format information only needs to be set once at first. On the other hand, when continuously reading different types of forms, since the format information differs for each form, it is necessary to identify the type of form each time and set the format information corresponding to the result.

[0005] Such processing is necessary when reading a very wide variety of forms one after another, such as at a bank or post office.

Therefore, generally, a method is used in which a dedicated identification code or mark is printed in advance at a predetermined position on a form, and format information to be set is determined based on the result of recognition of the code.

[0007] As an example of this, Japanese Patent Application Laid-Open No. 04-2704 entitled "Form identification method using facsimile OCR device".
No. 81 publication. According to this, a special mark is previously written on the left and right sides of a form, and identification is performed based on the interval between the two marks detected from the form image.

However, since it is not always possible to print a dedicated identification code or mark on all forms, a technique for identifying the form from the form image itself is also required. Japanese Patent Application Laid-Open No. 07-249099 entitled "Form Identification Device" is one example. In the device described in the above publication, focusing on the ruled line structure of a form, after separating characters and ruled lines from a form image,
In an image including only a ruled line and a background, a pixel projection distribution on a vertical axis is obtained and identification is performed.

In the following description, a form on which a dedicated identification code or mark is printed is abbreviated as an “ID form”, and a form on which these are not printed is abbreviated as a “non-ID form”.

When a non-ID form is identified by an image,
It is necessary to extract only information unique to the form from the image and use it for identification. Here, information unique to the form includes:
For example, a form title, a ruled line, a background pattern, a background color, and the like that have been printed in advance correspond to these (hereinafter, these are referred to as preprints). On the other hand, the information other than these includes the name and the amount entered by the user, the amount, the mark sheet, and the like, as well as the seal imprint.

[0011]

SUMMARY OF THE INVENTION The above-mentioned Japanese Patent Application Laid-Open No. 07-
In Japanese Patent No. 249099, identification using ruled lines, which is a kind of preprinting, is performed. However, since a process of extracting ruled lines from information of only an image requires a large amount of computation, it is not suitable for high-speed processing. there were. Further, when the image quality is poor and many breaks of the ruled line are included, or when the ruled line is in contact with the entered characters, an error occurs in the ruled line extraction, and the form may be erroneously identified.

In general, when identification is performed based on information other than ruled lines, for example, characters, it is necessary for the user to automatically identify the entered characters and the preprinted characters. It is necessary to manually select and register a preprinted character area in advance in order to use this for form identification, which has been pointed out as a disadvantage that it requires enormous labor.

[0013]

An object of the present invention is to improve the disadvantages of the prior art, and more particularly, to a form identification method capable of quickly and accurately identifying the type of a form from a form image not including a dedicated mark for form identification. It is an object of the present invention to provide a method and apparatus, and a medium recording a form identification program.

[0014]

In order to achieve the above object, according to the first aspect of the present invention, there is provided a step of taking in a form image and a step of extracting a handwritten area from the form image based on handwritten area information registered in advance for each form. Calculating a feature amount of a portion excluding a portion, a step of calculating an error amount between a feature amount of a portion excluding a handwritten area from the form image and a model feature amount registered in advance for each form, And determining the type of the form shown in the form image based on the error amount of the form.

According to the second aspect of the present invention, an image input unit for taking in a form image, a storage unit for storing handwritten area information and model feature amounts registered in advance for each form, and a form based on the handwritten area information Calculate the feature amount of the part excluding the handwritten region from the image, calculate the error amount between this feature amount and the model feature amount, and calculate the type of the form shown in the form image based on the error amount with the model feature amount. And a form identification unit that determines the

According to a third aspect of the present invention, there is provided a medium in which a program for identifying a form type by a computer is recorded, wherein the identification program causes a computer to read a form image, and a handwriting area registered in advance for each form. Based on the information, a feature amount of a portion excluding the handwritten area from the form image is calculated, an error amount between this feature amount and a model feature amount registered in advance for each form is calculated, and an error amount with this model feature amount is calculated. The type of the form shown in the form image is determined based on the form.

Here, the "form" includes a document such as a slip.

According to these inventions, the feature amount of a portion excluding the handwritten area from the form image is calculated, and this feature amount is compared with a model feature amount registered in advance. The model feature is
Several types of forms are registered in advance, and are compared with the respective model feature amounts, and are determined to be the same type as the model feature amount form with the smallest error amount.

With these, the above-mentioned object is to be achieved.

[0020]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below with reference to FIG.
This will be described with reference to FIG.

The form identification device shown in FIG. 1 includes an image input unit 1 for taking in a form image, a storage unit 2 for storing handwritten area information 2a and model feature amount 2b registered in advance for each form.
Based on the handwriting area information 2a, a feature amount of a portion excluding the handwritten area from the form image is calculated, and an error amount between this feature amount and the model feature amount 2b is calculated. And a form identification unit 3 for determining the type of the form shown in the form image based on the form.

More specifically, in this embodiment, the image input unit 1 is a scanner. The output image from the image input unit 1 is a full-color image, a black-and-white
Any image such as a value image may be used. In the following description, it is assumed that the form image is obtained as a monochrome gray-scale image. Here, the form image and the background image are included in the output of the scanner, but the background image is removed by the function of the form identification unit 3 described later, and only the form image is processed.

The storage unit 2 is, for example, a hard disk drive. Handwriting area information 2a stored in the storage unit 2
Is information in which the handwritten area is represented by coordinates or the like for several types of forms. For example, a portion surrounded by a thick line in FIG. 3C in the form image in FIG. 3A is a handwritten region, and the handwritten region information 2a is information describing the position of the handwritten region on the image. It is. The handwritten area information 2a can be selected and read for each type of form by designating a form number assigned to each type of form. On the other hand, the model feature value 2b is information in which the feature value of a part of the form image excluding the handwritten area is registered in advance for a plurality of types of forms. The type of the form is identified by comparing each model feature value 2b with a feature value calculated from an actually captured image.

Here, the feature amount used in general pattern recognition such as conventional character recognition, such as a blur feature, a direction feature, an edge feature, or a thinning feature, or a combination of these features is used. Can be used. For example, if the form image 100 is a color image, the color extraction image can be used in combination with the feature extraction.

The form identification unit 3 includes a microcomputer, and realizes various functions by executing a prepared form identification program. This form identification unit 3
Will be described later together with the operation description.
Reference numeral 4 denotes a memory for storing data required when the form identification unit 3 executes a process.

Next, the overall operation of this embodiment will be described with reference to FIG.

When a form is set in the image input unit 1 and an image capture request is input to the form identification unit 3, the form identification unit 3 drives the image input unit 1 to acquire a form image and a background image ( Step S1).

Subsequently, the form identification unit 3 removes the background image while leaving only the form image (step S2). As an algorithm of the background removal, for example, a method of separating and extracting a form portion and a background portion by performing a fixed binarization process after performing shading correction of an image can be used.

Next, the form identification unit 3 calculates the feature amount of the entire form image (step S3). Here, a case based on the blurring feature will be exemplified. Figure 3 shows the acquired form image
Assuming the image shown in (a), the form identification unit 3
As shown in FIG. 3B, the form image shown in FIG. 3A is divided into 5 × 4 grid areas, and the sum of the densities of the pixels included in each grid area is calculated, and this is used as a feature amount. In this case, 2
A zero-dimensional vector (a set of pixel densities for each grid region) is obtained. Here, the number of divisions is 5 × 4 and the number of dimensions is 20, but these conditions may be determined experimentally based on the image size, processing speed, and identification accuracy. Further, before calculating the feature amount, it is also possible to perform pre-processing such as image inclination correction and noise removal.

Next, the form identification unit 3 selects the form number of the form to be compared (step S4). The form numbers are serial numbers such as 1, 2, 3,..., And the storage unit 2 stores the handwritten area information 2a and the model feature amount corresponding to the different types of forms by the number of valid form numbers. 2b is registered. When the form number n is designated, the handwriting area information 2a and the model feature amount 2b corresponding to the n-th form form
Can be read. The form identification unit 3 updates the counter so that the form number is incremented by one each time the process of step S4 arrives,
Execute the following processing.

When the form number is set, the form identification unit 3
The corresponding handwritten area information 2a is read from the storage unit 2 (step S5), and the feature amount of the handwritten area corresponding to the form number is deleted from the feature amount of the form image calculated in step S3. In the handwriting area information 2a, for example, the position of the handwritten area in units of divided grid areas is described, and from this information, a vector in which 1 is given to an area other than the handwritten area and 0 is given to the handwritten area is configured. . For example, if the form image is now shown in FIG. 3 (c), the part surrounded by the thick line is the handwritten area. In this case, the vector formed from the handwritten area information 2a is the vector shown in FIG. Are represented by binary values of 0 and 1. Then, by multiplying this vector by the vector of the feature amount of the entire form image shown in FIG. 3B, the feature amount of the portion excluding the handwritten area as shown in FIG. Is done.

Here, the mask value in FIG. 3D is a binary value of 0 or 1, and this is used as a multi-valued mask, and the weighting results of the reading area and other areas are shown in FIG.
(E) is also possible.

The specific example of FIG. 3 shows a case where the captured form image matches the form of the set form number. However, depending on the set form number, the captured form image is not always The handwritten area information of the matching form is not always selected, and the feature amount of the preprinted part that is not the handwritten area may be deleted. For this reason, the pattern of the feature amount calculated in step S6 differs depending on the set form number (that is, the form type to be compared).

After calculating the characteristic values in this way, the form identification unit 3 reads out the model characteristic values 2b corresponding to the form numbers from the storage unit 2 (step S7). Model feature 2b
Is a pattern in which typical patterns of feature amounts that are to be calculated through the processing of steps S1 to S6 described above are registered in advance for a plurality of forms, and are managed by the form numbers described above. For example, for the form shown in FIG. 3A, FIG. 3E is registered as a model feature amount.

Subsequently, the form identification unit 3 collates the characteristic amount obtained by deleting the handwritten area corresponding to the form number calculated in step S6 with the model characteristic amount corresponding to the form number, and calculates an error amount thereof ( Step S8). If the selected form number does not match the type of the imported form image, an error occurs between the selected form number and the model feature amount. As the expression of the error amount, a similarity or a distance value can be used. For example, the feature amount calculated in step S6 is defined as a vector a and the exemplary feature amount is defined as a vector b, and a simple similarity S calculated by the following equation can be adopted. Here, | a | indicates the norm of the vector a.

S = (a, b) / (| a | − | b |) (1)

On the other hand, when matching is performed using distance values, the number of dimensions of both vectors a and b must be N, and a distance value D normalized by N must be used.

D = | ab | / N (2)

The reason is that the number of dimensions of the model feature amount vector differs depending on the type of the form, because the handwritten area to be removed in each form differs. In contrast,
Since the degree of similarity includes a normalization operation based on the number of dimensions N of the vector, this need not be separately considered.

Here, when expressing the error amount by the similarity or the distance value, the normalized similarity or the distance value may be experimentally selected according to the property or characteristic of the object. Instead of this, it may be expressed by something other than the similarity or the distance value. Other examples include a composite similarity and a mixed similarity.

The form identification unit 3 stores the calculated error amount in the memory 4 in association with the form number (step S9), and determines whether or not all form numbers have been collated (step S9). S10). As a result, if the collation processing has not been completed for all the form numbers, the next form number to be collated is selected (step S4).
The processing from step S5 to step S10 is repeatedly executed. On the other hand, when the collation is completed for all the form numbers, the form number having the smallest error amount (for example, if the similarity is high, the similarity is high) among the error amounts stored in the memory 4 is taken into the captured image. It is output as an identifier indicating the type of the indicated form (step S11).

As described above, according to the present embodiment, the type of the form is identified by comparing the characteristic amount of the portion where the handwritten area is deleted from the captured form image with the model characteristic amount. The type of the form can be accurately identified without being affected by the information. In addition, as compared with a case where a form is identified by extracting preprint information such as a ruled line from an image as in the conventional example, the reliability of identification can be improved and the amount of calculation can be reduced. High-speed identification processing can be performed at the job site. Furthermore, since the handwritten area information for each form is conventionally used in the character recognition process in the OCR, this existing information can be effectively used, and is economical.

Here, in the above-described embodiment, the "handwritten area" may include not only a handwritten character area but also a notation area of an artificially applied image such as an imprint. Needless to say, the present invention can be used for identification of documents such as slips other than forms. The identification program executed by the form identification unit can be recorded on a recording medium and traded.

[0044]

Since the present invention is constructed and functions as described above, according to this, the type of the form is identified by comparing the feature amount of the portion where the handwritten area is deleted from the captured form image with the model feature amount. Therefore, the type of the form can be identified with high accuracy without being affected by the state of the description of the handwritten area. In addition, as compared with a case where preprint information such as ruled lines is extracted from an image and a form is identified as in a conventional example,
Since the certainty of identification can be improved and the amount of calculation can be reduced, high-speed identification processing can be performed at a site such as a window business. Furthermore, since the handwritten area information for each form is conventionally used as format information in the character recognition process of OCR, this existing information can be effectively used, and it is not economically conventional. An excellent form identification method and apparatus and a medium recording a form identification program can be provided.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an embodiment of the present invention.

FIG. 2 is a flowchart showing the operation of the embodiment shown in FIG.

3A and 3B are explanatory diagrams for explaining the operation of the embodiment shown in FIG. 1. FIG. 3A is an example of a captured form image, FIG. 3B is an example of a feature amount extracted from the form image, and FIG. 3C shows the relationship between the form image and the handwritten region, FIG. 3D shows the vector for the mask created from the handwritten region information, and FIG. 3E shows the characteristic obtained by deleting the handwritten region from the feature amount of the form image. The amounts are indicated respectively.

[Explanation of symbols]

 Reference Signs List 1 image input unit 2 storage unit 2a handwriting area information 2b model feature amount 3 form identification unit 4 memory S form type information

Claims (3)

[Claims] A step of acquiring a form image; a step of calculating a feature amount of a portion excluding a handwritten area from the form image based on handwritten area information registered in advance for each form; Calculating an error amount between the feature amount of the portion excluding the region and the model feature amount registered in advance for each form; and a type of the form shown in the form image based on the error amount from the model feature amount. Identifying the form. 2. An image input unit for taking in a form image, a storage unit for storing handwritten area information and model feature amounts registered in advance for each form, and a handwritten area from the form image based on the handwritten area information. Is calculated, and an error between the feature and the model feature is calculated, and the type of the form shown in the form image is determined based on the error between the model feature and the model feature. A form identification device, comprising: 3. A medium in which a program for identifying a type of a form by a computer is recorded, wherein the identification program causes the computer to capture a form image, based on handwritten area information registered in advance for each form. A feature amount of a portion excluding the handwritten area is calculated from the form image, an error amount between this feature amount and a model feature amount registered in advance for each form is calculated, and based on an error amount with the model feature amount. A medium on which a form identification program is recorded, wherein the type of the form shown in the form image is determined.