JPS6083468A - Binary coding device for picture signal - Google Patents

Abstract

PURPOSE:To optimize the binary coding of a part where density variation is large by calculating a threshold value on the basis of the mean density value of picture elements, and correcting the threshold value with the deviation threshold value obtained by deviating the calculated threshold value by the specific number of picture element in the opposite direction of a scanning direction. CONSTITUTION:A picture signal deviation part 2 and a mean value deviation part 3 deviates a density signal Px and a mean value Ma both in a scanning direction by the number of picture elements corresponding to the width of an area A to generate a deviation density signal Pxd and a mean deviation value Mad. A mean value selection part 4 selects a larger value between the mean value Ma and mean deviation value Mad for every picture element to generate a corrected mean value Ms, which is applied to a threshold arithmetic part 5 to calculate the threshold value TH on the basis of the corrected mean value Ms. This threshold value TH is applied to a binary coding circuit 6 and converted into a binary-coded signal SB, which is outputted to a next-stage device.

Description

DETAILED DESCRIPTION OF THE INVENTION [Technical Field] The present invention relates to a dual-signal binarization device that properly binarizes both signals even if the density of the background of a document changes.

[Prior art] In order to divide an image on a document whose background color or density has partially changed, such as a pasted document, a mixed-picture document, or a color document, into pixels and convert it into a binary image, a binary method is required. It is necessary to change the threshold value for image processing according to the background color and density of the document.

Conventionally, the density level signal of each pixel is divided at a predetermined ratio using a dividing resistor, the divided signal is low-pass filtered to form a so-called floating threshold, and the density level signal is binarized using this floating threshold. A device that does this is in practical use.

However, since such conventional devices use a time constant element for low-pass filtering, it is not possible to sufficiently follow density changes, especially in areas where the density of the background increases rapidly, such as at the border of the pasted part of the original. Another problem is that the threshold value cannot be set with high precision.

[Purpose] The present invention has been made in order to eliminate the drawbacks of the prior art described above, and it calculates a threshold value based on the average density value of pixels, and biases this threshold value in the anti-scanning direction by a predetermined number of pixels. To provide an image signal binarization device that can appropriately binarize both signals in a part where density changes are large, such as a part where density rapidly increases, by correcting a threshold value with a shifted threshold value. With the goal.

[Configuration] Hereinafter, embodiments of the present invention will be described in detail based on the accompanying drawings.

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

In the figure, an average value calculation unit 1 calculates the average value Ma of the density around the pixel to be binarized (hereinafter referred to as the pixel of interest) based on the density signal (image signal) Px for each pixel added from the scanner. Calculated using formula N).

Ha = (1m)S o +mMa' --(1) However, So is the density of the pixel of interest, ■1 is the weighting coefficient, and To1a
' is the average value when the immediately previous pixel is the pixel of interest.

This equation (1) will be explained below.

Generally, there is a correlation between the density of a pixel of interest and the density of a pixel located near the pixel of interest (hereinafter referred to as a reference pixel). , and the correlation between concentrations is also strong.

Therefore, the weighted average value calculated by assigning a weighting coefficient that decreases exponentially as the distance from the pixel of interest increases to each reference pixel according to its distance is:
This reflects the density distribution, that is, the background density of the image near the pixel of interest.

Therefore, by performing a predetermined calculation (for example, conversion using a linear function) on this weighted average value, a threshold value that reflects the background density can be obtained.

Now, let the density of the pixel of interest be S and o, and the density and weighting coefficient of the reference pixel that is located a distance (i x r) (i is an integer, r is the width of one pixel) from the pixel of interest are Si and $, respectively.
When (0<m<1), the weighted average value Ma of the reference pixels including the pixel of interest is expressed by the following equation (n).

1++++10+l+2 +...10m1 This formula (
By transforming II), the following formula (m) is obtained.

Here, since ml-0, the above formula (III) becomes as follows.

Ma=(1-m)S o 10 mMa' In this way, the above formula (1) is obtained.

Since equation (1) takes the form of an incremental equation, the average value calculation section 1 that calculates the average value Ma using equation (1) has a very simple circuit configuration. However, since the density state of each pixel is not directly used, it has some delay characteristics.

For example, the concentration signal P shown by the solid line in FIG. 2(a)
If x is added, the average value calculation section 1 outputs the average value Ma as shown by the dashed line in the figure.

In this example, the influence of the delay of the average value Ma is strongest in the area A in the figure where the density signal Px rises, and if the threshold value is calculated using this average value Ma, this area will be judged as completely black. Sometimes.

Therefore, in this embodiment, first, the image signal deviation section 2 and the average value deviation section 3 scan the density signal Px and the average value Ma by the number of pixels corresponding to the width of the area A. and the deviation concentration signal P as shown in FIG. 2(b)
xd and a deviation average value Mad.

Then, the average value selection unit 4 selects the larger of the average value Ma and the deviation average value Mad for each pixel to form a corrected average value Ms as shown in FIG. 2(c).

This corrected average value MS is added to the threshold calculation section 5.

The threshold calculation unit 5 calculates the corrected average value Ms by the following equation (IV).
The threshold value Tll is calculated based on.

TH=k1・Ma+k2...-(IV) However, 2 is a coefficient in k+.

The threshold value TH is applied to the binarization circuit 6. by this,
The deviation concentration signal P'xd is binarized using a threshold value TH, converted into a binarized signal S8, and outputted to a next-stage device (not shown).

Therefore, the binarized signal SB becomes one in which the above-described disadvantages in area A are resolved.

In the embodiment described above, both the average value Ma and the density signal Px are deviated in the scanning direction of the scanner, a modified average value Ms is formed from the average value Ma and the deviation average value Mad, and based on this modified average value Ms. Although the threshold value T11 is calculated using the above method, the present invention is not limited to this.

For example, only the average value Ma may be shifted in the counter-scanning direction of the scanner to form a modified average value. Also, the average value is 14
3 is a block diagram showing another embodiment of the present invention.

In this embodiment, the average value Ma calculated by the average value calculation section 1 is directly added to the threshold value calculation section 5.

The threshold calculation unit 5 calculates the threshold TH+ (see FIG. 4(a)) based on the above formula (IV), and applies this to the threshold deviation unit 7 and the threshold correction unit 8.

The threshold deviation unit 7 deviates the threshold Ttl+ by a predetermined number of pixels in the counter-scanning direction of the scanner to form a deviation threshold r++d as shown in FIG. Add to.

The threshold correction unit 8 compares the threshold TH+ and the deviation threshold TI(d for each pixel, selects the larger one, and sets this as the correction threshold THm.
(See FIG. 4(c)) is output to the binarization circuit 6.

Therefore, the inconvenience that the rising edge portion of the density signal Px is determined to be completely black is resolved.

Note that the two embodiments described above can also be realized in software using a microcomputer.

[Effects] As explained above, according to the present invention, a threshold value is calculated using the average value of the peripheral density of each pixel, and a deviation threshold value is formed by shifting this threshold value in the counter-scanning direction of the scanner, Since the threshold value is corrected using this deviation threshold value, there is an advantage that a portion where the density suddenly increases can be binarized appropriately.

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing one embodiment of the present invention, and FIG. 2 (
(a) is a waveform diagram illustrating the concentration signal and average value; (b)
3 is a waveform diagram illustrating the average value, deviation average value, and deviation concentration signal; FIG. 3(c) is a waveform diagram illustrating the corrected average value and concentration signal; FIG. Block diagram, FIG. 4(a) is a waveform diagram illustrating the concentration signal and threshold value,
FIG. 5B is a waveform diagram illustrating a density signal, a threshold value, and a deviation threshold value, and FIG. 1... Average value calculation section, 2... Image signal deviation section, 3...
Average value deviation section, 4... Average value selection section, 5... Threshold value calculation section, 6... Binarization circuit, 7... Threshold value deviation section, 8.
...Threshold correction section. [i Figure 2 Figure 4

Claims (1)

[Claims] (]) In an image signal binarization device that binarizes an image signal sequentially output from a pixel decomposition type scanner into black and white pixels,
an average value calculation means for calculating the average value of the density of a pixel of interest to be converted into a value and a plurality of reference pixels consecutive to the pixel of interest; and a scanner that uses the average value and image signal calculated by the average value calculation means for a predetermined number of pixels. signal deflection means for forming a deviation average value and a deviation image signal shifted in the scanning direction; and average value selection means for selecting the larger of the average value and deviation average value for each pixel; An image signal binarization device comprising threshold calculation means for calculating a threshold value for each pixel based on the output of the average value selection means, and for binarizing the deviation image signal using the threshold value. (2. In claim 1, the average value calculating means is configured to calculate a weighted average value by assigning to each reference pixel a weighting coefficient that becomes exponentially smaller depending on the distance from the pixel of interest. An image signal binarization device characterized by performing calculations. (3) In an image signal binarization device that binarizes an image signal sequentially output from a pixel decomposition type scanner into black and white pixels,
an average value calculation means for calculating the average value of the density of a pixel of interest to be converted into a value and a plurality of reference pixels consecutive to the pixel of interest; and a threshold value for each pixel is calculated based on the average value calculated by the average value calculation means. a threshold calculation means for calculating the threshold value by a predetermined number of pixels with respect to the image signal in the anti-scanning direction of the scanner; An image signal binarization device characterized by comprising a threshold value correction means for calculating a corrected threshold value based on a position threshold value.