Code image quality checking device

Details Code image quality checking device Code image quality checking device

1999-06-03

2003-07-01

Lee, Thomas D. (Department: 2624)

Image analysis

Image enhancement or restoration

C382S181000

Reexamination Certificate

active

06587591

ABSTRACT:

BACKGROUND OF THE INVENTION
The present invention relates generally to an information recording medium having an area which is optically readably printed in a given format with a code image comprising an arrangement of a plurality of dots corresponding to data containing at least information such as sound, video and text. More particularly, the present invention relates to a system for checking the quality of such a code image.
For example, in published European applications EP 670,555 and 717,398 assigned to the same assignee as this application are disclosed a dot code which is a code image for allowing data containing information, such as sound, video, or text, to be optically readably printed at high density in a given format and a code image reading device for optically reading the dot code by an operator's manual scanning operation and reproducing information such as original sound.
Here,
FIG. 8
shows a physical format of such a dot code.
As shown in
FIG. 8
, a dot code
100
, representing information, such as sound, in the form of an arrangement of dots, is two-dimensionally divided into a plurality of blocks
101
. Each block is composed of a data area
103
, markers
102
, a pattern dot area
104
, and a block address pattern area
105
.
In the data area
103
of each block there exists data as a dot image of white or black dots indicative of 0s or 1s arranged in a predetermined format. The markers
102
are used to find a reference point for detecting each dot in the data area and are located at four corners of each block. These markers, defining the blocks, are arranged at regular intervals from top and bottom and from left to right. In each block, its associated pattern dot area
104
is located between the left-side markers
102
and its associated block address pattern area
105
is located between the bottom markers and has an error detecting or correcting code. The block address pattern area is used to identify the corresponding block in a read operation.
FIG. 9
shows a block diagram of the conventional code image reader for optically reading the dot code
100
.
As shown in
FIG. 9
, the code image reader comprises an imaging unit
201
, an image memory
202
, a binarization unit
203
, an image memory
204
, a restoration unit
205
, and a reproduction unit
206
. In more detail, the restoration unit
205
comprises a center-pixel-in-dot detecting section
205
a
and a dot decision section
205
b
, and the reproduction unit
206
comprises a demodulation section
206
a
, an interleave memory
206
b
, an interleave and error correction section
206
c
, and an output section
206
d.
The imaging unit
201
is equipped with an illumination section having a light emitting diode (LED) for illuminating the dot code
100
, a solid state imaging device such as a charge coupled device (CCD), and an optical system for focusing reflected light from the dot code onto the CCD. The image memory
202
subjects an image signal output from the imaging unit to digitization and then stores the resulting digital image signal. The binarization unit
203
subjects the digital image signal read from the image memory
202
to thresholding for binarization. The image memory
204
stores the resulting two-valued image data from the binarization unit
203
. The restoration unit
205
detects dots from the two-valued image data read from the memory and allocates a value of either 0 or 1 for each dot to thereby output dot arrangement data. The reproduction unit
206
is responsive to the dot arrangement data from the restoration unit to reproduce the original information such as sound.
The code image reader thus arranged, even if the size of the entire dot code is larger than the field of view, or the imaging area
100
a
,
100
b
of the imaging unit
201
, allows the dot code to be read by scanning each of consecutive image regions in sequence by manually moving the imaging unit
201
over the code image in the direction indicated by an arrow.
That is, even if the entire dot code
100
cannot be imaged at one time, the original data can be reconstructed from dot arrangement data in each block
101
if the address assigned to each block can be read and recognized correctly.
Thus, the code image techniques described above allow a lot of information to be stored at high densities on media such as paper, which is impossible with conventional one-dimensional or two-dimensional bar codes. The techniques, which allow easy transfer of information, such as sound, through paper, have been increasingly expected to find extensive applications which have not been supposed so far.
Here, the binarization unit
203
is arranged to control adaptively the threshold value for binarization according to printing conditions of the code image, for example, the density of white dots (paper surface) or black dots. Even if the printing quality of the code image is somewhat bad, therefore, an appropriate operation is performed accordingly.
In reading the two-valued image data from the image memory
204
and detecting dots, the restoration unit
205
is arranged to control adaptively the reference points for detecting the dots according to printing conditions of the code image, i.e., printing displacements of the dots and their deformation. As in the binarization unit
203
, even if the printing quality of the code image is somewhat bad, the restoration unit performs an appropriate operation accordingly. The restoration unit, which is basically constructed from the central-pixel-in-dot detecting section
205
a
and the dot decision section
205
b
, first detects the markers
102
and then, on the basis of the pattern dot reading reference point determined by the detected markers and format information, searches the pattern dot area
104
for each dot and computes the dot detecting reference point for which an error function defined by distances between the ideal centers of dots constituting the pattern dot area
104
and the centers of the corresponding dots actually searched for is minimized.
This search operation is described in Japanese Unexamined Patent Publication No. 8-171620.
The restoration unit further detects the central pixel in each dot on the basis of the detecting reference point thus computed, decides whether the detected dot is black or white, allocates a value of either 1 or 0 for the detected dot, and outputs dot arrangement data. Thus, even if the printing quality of the code image having dots printed at high density is bad, the code image can be read quite satisfactorily.
Such code images will be printed under various printing conditions including various types of printing machines, various printing materials such as paper and inks, and printing machine management methods. Thus, in order to allow code images to be read stably at all times, it is required to maintain always the printing quality of code images themselves constant.
In general, the quality control of conventional bar codes is performed on the basis of the width and the density or contrast of bars specified in JIS standards JIS X 0501, 0502 and so on.
Specifically, the quality is checked using a checking device as disclosed in, for example, Japanese Unexamined Patent Publication No. 5-77530.
As described above, however, in a code image reader for optically reading a code image having dots printed at high density, such as dot code
100
, even if the printing quality of the code image is not good, the binarization unit
203
and the restoration unit
205
operate adaptively to read the code image successfully. Thus, the utilization of the bar code checking method for code images without modification results in an increase in the checking time and the size of the checking device. In addition, the checking method is no longer suitable for checking devices for checking high-density code images. Therefore, there arises need to establish anew a quality checking method that is the most suitable for high-density code images.
From a standpoint that the original purpose of checking the quality of a code image itself is to confirm whet

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