JPH11279936A - Creping capability measurement system for creped woven fabric and creping capability measurement - Google Patents

Abstract

PROBLEM TO BE SOLVED: To measure the creping capability of a creped woven fabric easily, objectively, quantitatively, and accurately by taking hold of the yarn part of the creped woven fabric as the contour part of its photographed image and calculating the directional distribution of the yarn part. SOLUTION: This measurement system works as follows: a creped woven fabric is photographed using a magnifying glass-mounting type CCD camera 1, the resulting image is inputted into an image analyzer 2, an edge detection is conducted using a primary differential operator followed by binary processing and then line-thinning processing to accurately determine the contour part of the image; the direction of the edge is measured using contour-contg. picture elements alone, the distribution frequency is determined at intervals of 10 degree, and the degree of orientation is calculated by function formula; the analysis result thus obtained is delivered, together with the original image, to an engineering work station where the analysis result for the directional distribution is presented as a graphic pattern and displayed on a monitor 5 together with the value of the degree of orientation and the original image.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and a method for measuring creasing of crimped fabric, which objectively and quantitatively evaluates crimping of crimped fabric.

[0002]

2. Description of the Related Art Conventionally, evaluation of the crimping property of a crimped fabric used as an inspection standard for fabric inspection is described in Japanese Patent Application Laid-Open No. 62-2233.
As shown in Japanese Patent Application Laid-Open No. 19-1932 and Japanese Patent Application Laid-Open No. 5-263315, this is merely expressed by expressions such as good and bad and vague expressions such as double circles, triangles, and crosses. It was unclear how it was improved and how it was defective. In addition, this determination often depends on experts who are good at texture evaluation, and it is easy to be subjective, and there are many variations among evaluators, which makes it difficult to obtain an objective evaluation.

The method of Matsumoto and Tosada, et al., Journal of the Japan Textile Machinery Society, 37, (1984) p. According to 471, the number of ridges and the height of the ridges are measured from the cross-section of the fabric, but skill is required to determine and measure the ridges, and only one-dimensional information can be obtained at a time. There is a disadvantage that it cannot be done.

According to JP-A-8-302561, the distance between the intersections of the warp and the weft on the woven fabric surface is continuously measured at least 20 points in the weft direction, and the crimping factor value calculated from the equation is used. Although the crimp standing property is evaluated objectively, in the case of a weft that is visible or hidden on the surface of the fabric, it cannot be confirmed whether the weft is the measured weft. That is, there are problems such as the inability to continuously measure in the weft direction and the inability to confirm the intersection.

In addition, Mizoguchi's method, Japanese Textile Machinery Society Hokuriku Chapter research presentation and special lecture abstracts (December 1996
5) According to 1, the difference in the degree of the bright and dark portions of the grain and the difference in the density of the grain interval are quantified from the luminance information of the image analysis to quantitatively evaluate the grain texture, which was used in this report. Wrinkled woven fabrics are limited to Yangyangi type and deshin type represented by weft strong twist yarn, and image processing is performed by replacing the subtle visual differences in the grayscale image of the woven fabric with the degree of crimp standing. If the evaluation is obscured or the unevenness of the fabric surface is small, the difference between the light and dark areas will be small, and even though the fabric is visually flat with fine grain, it will be evaluated as a flat fabric There are drawbacks such as obtaining inconsistent results.

[0006]

Even when the graininess is measured using the above-described evaluation method, there is a problem in the assumed accuracy, and further improvement in the measurement accuracy is required.

Accordingly, an object of the present invention is to improve such conventional disadvantages and to make it industrially easy, objective and quantitative.
Still another object of the present invention is to provide an apparatus and a method for measuring the crimp standing property of a crimped fabric, which can be performed by anyone with high accuracy by quantifying the degree of undulation of the yarn provided in the crimped fabric.

[0008]

In order to achieve the above object, according to the present invention, there is provided a photographing means for photographing a textured fabric, and a contour image in an image obtained by the photographing means, wherein the contour image is obtained. A thread part detecting means for detecting a thread part forming a woven fabric, an image analyzing means for acquiring a direction of the detected thread part, and an information processing means for calculating a distribution of a plurality of thread parts in the acquired direction. The direction distribution obtained by the information processing means is used as a measurement result of crimp standing of the crimped fabric.

According to a second aspect of the present invention, in the apparatus for measuring the crimping property of the crimped woven fabric according to the first aspect, the image analyzing means performs a thinning process on the contour image detected by the yarn portion detecting means. After the application, the direction of the thread portion is obtained.

According to a third aspect of the present invention, in the first aspect of the present invention, the information processing means further converts the value of the directional distribution into a frequency.

According to a fourth aspect of the present invention, there is provided a yarn portion detecting step of detecting an outline image from a textured fabric image as a yarn portion forming the textured fabric by an image analyzer, and determining a direction of the detected thread portion. An image analysis step of acquiring by the image analysis device; and an information processing step of calculating, by the image analysis device, a distribution of a plurality of thread portions in the acquired direction. It is characterized in that it is a measurement result of the crimping property of the woven fabric.

According to a fifth aspect of the present invention, in the method for measuring the crimping property of the crimped woven fabric according to the fourth aspect, the image analysis step performs a thinning process on the contour image detected by the yarn portion detecting means. After the application, the direction of the thread portion is obtained.

According to a sixth aspect of the present invention, in the method for measuring the crimping property of the grained fabric according to the fourth aspect, the value of the direction distribution is further converted into a frequency in the information processing step.

[0014]

Embodiments of the present invention will be described below in detail with reference to the drawings.

The present inventors measure the warp or weft constituting the fabric and the yarn axis direction angle in a minute section of the warp using a CCD camera and an image analyzer, analyze the measurement result, and By quantifying the calculated values, it was found that the graininess was objectively evaluated, and the present invention was achieved.

FIG. 1 shows a system configuration of a textile measuring apparatus to which the present invention is applied.

In FIG. 1, an image signal obtained by photographing a fabric to be inspected (hereinafter, referred to as an object) by a CCD camera 1 with a magnifying lens is sent to an image analyzer 2. This image signal is converted into a digital image by an A / D converter provided in the image analyzer 2. The digital image is stored in an image memory in the image analysis device 2 and displayed on the high definition monitor 3.

The resolution of the CCD camera 1 may be 250,000 pixels or more. The magnification of the magnifying lens is preferably 10 to 50 times.

The measurement of the angle distribution in the yarn axis direction of the object, the frequency distribution of the edge direction distribution, and the quantification of the degree of embossing are executed by the image analyzer 2. More specifically, image data in an image memory provided in the image analysis device 2 is stored, and the
Performs image processing shown in the flowchart of FIG. By displaying the processed image on the high-definition monitor 3 by superimposing the original image (the image taken by the CCD camera 1), the original image and the measurement result can be confirmed at the same time. Inspection (including measurement) based on
Can be performed at high speed and with high accuracy. The result processed by the engineering workstation 4 is displayed on the monitor 5 and printed out from the printer 6 as necessary.

FIG. 2 is a flowchart showing an outline of a measurement procedure for performing image analysis. Each processing shown in this processing procedure is actually described in a program which can be read and executed by a computer, and is stored and stored in a recording medium of each of the image analysis device 2 and the engineering workstation 4, for example, a hard disk storage device. Workstation 4 and image analysis device 2
Is executed in accordance with the processing content by each of the CPUs. FIG.
1 is a schematic enlarged image of a woven surface of a weft woven georgette represented by a crimped woven fabric. The processing of the textile inspection device of FIG. 1 will be described with reference to the flowchart of FIG. 2 and the explanatory diagram of FIG.

First, prior to the inspection, the crimped fabric of the object is placed on the monitor 5XY plane so that the center axis of the warp (indicated by a solid line) is at an angle of 45 degrees with respect to the X axis as shown in FIG. An examiner places the sample on a sample table (not shown) (see the dashed line in FIG. 3). For this reason, the center axis of the weft is 1 to the X axis.
It is arranged at an angle of 35 degrees (see the dashed line in FIG. 3). Next, the entire inspection apparatus is operated, an object is photographed by the magnifying lens-attached CCD camera 1, and the obtained image is input to the image analysis apparatus 2 (step S1).

In step S2, the image analysis apparatus 2 performs edge detection by a primary differential operator in order to detect the contour of the object. That is, the direction θ of the edge with respect to the X axis is measured at minute intervals (several tens of microns) on the contour of the yarn. The edge direction θ is as shown in FIG. 4, and the measurement point of the edge direction θ varies depending on the specifications of the CCD camera 1 to be used, but is approximately several thousands to tens of thousands of points.

In step S3, the image analyzer 2 performs a binarization process to separate the outline of the object from the background.

In step S4, since the outline obtained by the binarization processing has a certain line width, a thinning processing for reducing the outline of the image to a line having a line width of 1 is performed in the image analyzing apparatus 2, and the outline of the captured image is obtained. The contour of the object is accurately determined.

In step S5, the image analyzer 2 measures (calculates) the direction θ of the edge using only the pixels including the contour. Here, the measured direction of the edge of the yarn contour is such that the warp is inclined 45 degrees with respect to the X-axis, so that the variation in the direction of the edge that the warp can take is zero around 45 degrees.
The range is from 90 degrees to 90 degrees, and the variation in the direction of the edge that can be taken by the weft is 90 degrees to 180 degrees with the center at 135 degrees.
Therefore, it should be noted that the distribution in the direction of the edge in FIG. 5 is a normal distribution in the direction of the warp edge having a peak at 45 degrees and a normal distribution in the direction of the weft edge having a peak at 135 degrees.

In step S6, the image analyzing apparatus 2 determines that the direction of the warp edge is 0 to 90 degrees and the direction of the weft edge is 90 degrees.
For each distribution of ~ 180 degrees, every 10 degrees
Find the distribution frequency. Here, since the frequency value in the direction of the most frequent edge is 1, the frequency value of the other edges in the direction θ range is 1 or less.

In step S7, the image analysis device 2 calculates a functional expression using the obtained frequency value, and defines the obtained value as the degree of orientation.

The above image analysis processing is executed by the image analysis apparatus 2, and the analysis results obtained so far are transferred to the engineering workstation 4 to the original image of the object. The engineering workstation 4 makes the analysis result of the directional distribution graphical in the form of a graph. The created orientation distribution measurement graph and the orientation value obtained from the analysis result are displayed on the monitor 5. The original image is also displayed on the monitor 5 together with the above-described graph and numerical values.

Although the individual image analysis processes described above are well known, they are related to the present invention, and the related processes will be described in detail.

(1) Edge Detection Processing by Primary Differential Operator In order to detect an image portion forming a line or an outline in the entire image, a portion where the shading changes rapidly is recognized as an edge. , And differentiates the density of the image data. In the case of a digital image, the derivative can actually be determined as a difference. The difference H (x, y) in the horizontal direction and the difference V (x, y) in the vertical direction are obtained by the primary differential operator shown in FIGS. FIG. 6 shows a horizontal difference operator, and FIG. 7 shows a vertical difference operator.

If I (x, y) is a density value at a point (x, y) in the original image, H (x, y) and V (x, y) are as follows.

[0032]

## EQU1 ## H (x, y) = I (x + 1, y-1) + 2I
(X + 1, y) + I (x + 1, y + 1) − ｛I (x−
(1, y-1) + 2I (x-1, y) + I (x-1, y +
1)｝

[0033]

V (x, y) = I (x + 1, y-1) + 2I
(X, y−1) + I (x + 1, y−1) − ｛I (x−
1, y + 1) + 2I (x, y + 1) + I (x + 1, y +
1)｝ From this, the magnitude of the concentration gradient E (x, y) is

[0034]

## EQU3 ## E (x, y) = {H (x, y) ² , V (x, y) ² }, and the direction of the gradient is as follows.

[0035]

Tan ^-1 V (x, y) / H (x, y) Since the direction θ (x, y) of the edge is perpendicular to the direction of the gradient, it is given by the following equation.

[0036]

[Mathematical formula-see original document] θ (x, y) = V (x, y) / H (x, y) + π / 2 Next, the difference H (x, y) in the horizontal direction by the primary operator
And how to determine the vertical difference V (x, y) will be described. Paying attention to a point (x, y) in the original image, and assuming that I (x, y) is a density value of the point as shown in FIG.
y) and V (x, y) are obtained by calculating the sum of products (1) and (2) of the density values near 8 of I (x, y) and the first-order differential operators shown in FIGS. )I do.

By the product-sum operation of the equations (1) and (2),
The difference at the point (x, y) is determined. Similarly, a differential image can be obtained by performing a product-sum operation on all points in the original image.

(2) Binarization Processing Since the image subjected to the first-order differentiation processing includes an effect other than the object, binarization is performed to separate only the outline of the object from the background.

The binarization of an image is performed by the following threshold processing.

(TH is a threshold value)

[0041]

E (x, y) = 1: E (x, y) ≧ TH

[0042]

E (x, y) = 0: E (x, y) <TH (3) Thinning The binary image obtained by performing edge detection and binarization processing on the original image is a first derivative Since the value has a width, it is a figure of a contour of a fiber having a certain width, and is therefore reduced to a line width of 1 by a thinning process. The line width 1 is a unit of the width of one pixel.

The image processing for thinning basically takes the form of "erasing all pixels which are erasable elements and are not end points of the line from the boundary points in the image". This image processing is repeated until there are no more pixels to be erased.

(4) Degree of orientation <Degree of warp orientation>

[0045]

(Equation 8)

Warp orientation = 2.24 LN (A) +1 (A> 0) N: Number of angle divisions (9) fθn: Number of distributions of θn (normalized so that the sum is 1) Angle range: 0 Degrees or more and less than 90 degrees <weft orientation degree>

[0047]

(Equation 9)

Warp orientation = 2.24 LN (−B) +1 (B <0) N: Number of angle divisions (9) fθn: Number of distributions of θn (normalized so that the sum is 1) Angle range: The orientation degree value obtained from the equation of 90 degrees or more and less than 180 degrees takes a value of 0 to 1 and a value of 1
Means that the direction of the edge is distributed only in a certain direction. If the value is 0, the direction of the warp edge is 0 to 9 in the case of warp.
In the case of weft, it means that the weft direction angle is equally distributed in all directions of 90 to 180 degrees. That is, by replacing the degree of waviness of the yarn that governs the crimping property of the crimped fabric with a value of the orientation degree of 0 to 1, it is possible to accurately quantify the crimping property of the warp and the weft. In addition, the uniformity of the graining can be known from the variation in the degree of orientation.

The point (x, y) is calculated by the first derivative operator.
Is obtained, and a contour image E (x, y) of the object is obtained by binarization and thinning processing (E (x, y) = 1 on the contour line, Otherwise, E (x, y) = 0).

Hereinafter, the present invention will be described in detail with reference to Examples and Comparative Examples.

(Other Embodiment) FIG. 9 shows a system configuration of another embodiment to which the present invention is applied. In FIG. 9, 7
Denotes a sample table, and the sample table 7 has a movable slide rail 9. Therefore, the operator can change the cloth photographing position without touching the cloth 8. 1
Reference numeral 0 denotes a magnifying lens-attached CCD camera for photographing a fabric. In this example, a resolution of 250,000 pixels was used, and a magnifying lens magnification was 25 times.

Reference numeral 11 denotes a main body of the image analysis apparatus, and reference numeral 12 denotes a printer for outputting an analysis result. Reference numeral 13 denotes a monitor for displaying an image. In this embodiment, the function of the engineering workstation 4 in the above-described embodiment is also executed by the image analysis device 2. Also, the image analysis device main body 1
1 is that evaluation (ranking) is performed on the image analysis result.

Using the above system, quantitative evaluation of crimp standing was performed on 16 crimped fabrics, and the results were compared with the results of sensory evaluations by 20 monitors.

The grain fabric used here is as shown in Tables 1 and 2. For quantitative evaluation, the degree of orientation was determined by image analysis. In addition, the sensory evaluation was evaluated in four steps of □, ○, Δ, ×, in the order of increasing grain standing.

The sample No. Nos. 1 to 8 are crimped fabrics desin using a weft twisted yarn as the warp non-twisted yarn, and the evaluation results are shown in Table 1. Sample No. Nos. 9 to 16 are woven georgettes using a warp and a weft shared twist, and the evaluation results are shown in Table 2.

In Table 1, NO. Nos. 8 and 6 were evaluated as □, and NO. 5 and 1 were evaluated as x. In addition, NO. 3 and 7 are 、, NO. 2, 4
Was evaluated. In Table 2 as well, those having a small degree of orientation are the same as those in Table 1, and those having a large degree of orientation are X. From this, it can be understood that the graining property evaluation method of the present invention has a correlation with the conventional subjective evaluation, and that the graining property is small when the orientation degree value is small. Furthermore, while the sensory evaluation was a four-step evaluation, the degree of orientation could be evaluated steplessly, and it was confirmed that the evaluation accuracy was high.

[0057]

[Table 1]

[0058]

[Table 2]

The following embodiment can be carried out in addition to the above-described embodiment.

1) In the above-described embodiment, the apparatus for quantifying the crimping property of the crimped fabric has been described. However, this apparatus can be used as a measuring device for crimping property or an inspection device for fabrics. When used as an inspection device, a threshold value that determines the pass or rejection of the product quality is determined in advance, and the measurement result of the grain standing property obtained by the image analysis device is compared with the threshold value. In some cases, the image analysis apparatus may make a pass judgment, and if not in the allowable range, a reject judgment.

2) Although the above embodiment is a system fixed on the ground, a measuring device that can be configured using a CCD camera (video camera) and a small image analyzer (for example, a notebook personal computer) is used. You may comprise.

3) In the above-described embodiment, the form in which a dedicated image analysis device is used has been described. However, a general-purpose personal computer or an information processing device capable of executing an image analysis program may be used as the image analysis device. it can.
Further, an image analysis program for measuring graininess is recorded on a readable recording medium such as a CDROM or a floppy disk, and is mounted on the information processing apparatus.
An image analysis program may be executed.

4) The image of the grain fabric to be measured does not need to be directly input from the photographing device, but may be transferred to the image analysis device indirectly via communication from another computer or via a portable recording medium.

[0064]

As described above, according to the first and fourth aspects of the present invention, the grain portion of the grain fabric is regarded as the contour portion of the photographed image, and the directional distribution thereof is calculated to obtain the grain standing property of the grain fabric. Is quantified (measurement result). This makes it possible to objectively, quantitatively, and precisely measure the crimp standing property of any grain fabric. At the time of measurement, no human intervention is required, and there is no individual difference visually. Anyone can easily determine the graininess. Furthermore, by using the quantified orientation degree value and the variation of the orientation degree, it is possible to statistically grasp the relationship between the properties of the original yarn and the properties of the twisted yarn, and to determine the production conditions of the original yarn and the twisted yarn. Useful.

According to the second and fifth aspects of the present invention, by thinning the contour image, the direction of the yarn, that is, the inclination, can be easily obtained from two or more points on the line.

According to the third and sixth aspects of the present invention, the degree of graininess can be easily understood by converting the value of the direction distribution into a numerical value representing a level.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a system configuration of a measuring device according to an embodiment of the present invention.

FIG. 2 is a flowchart showing an outline of a measurement procedure for performing image analysis.

FIG. 3 is an explanatory diagram schematically illustrating a schematic enlarged image of a woven fabric surface of a warp-twisted woven georgette.

FIG. 4 is an explanatory diagram showing the direction of an edge.

FIG. 5 is an explanatory diagram showing a graph illustrating an example of a frequency ratio in the direction θ of the edge of a warp and a weft;

FIG. 6 is an explanatory diagram showing a difference in a horizontal direction by a first derivative operator.

FIG. 7 is an explanatory diagram showing a difference in a vertical direction by a first derivative operator.

FIG. 8 is an explanatory diagram showing density values of an original image.

FIG. 9 is a block diagram illustrating a system configuration according to another embodiment.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 (Magnifying lens attached type) CCD camera 2 Image analyzing device 3 High definition monitor 4 Engineering workstation 5 Monitor 6 Printer 7 Sample stand 8 Textile 9 Slide rail 10 Magnifying lens attached type CCD camera 11 Image analyzing device 12 Printer 13 Monitor

Claims (6)

[Claims] 1. A photographing means for photographing a grain fabric, a thread part detecting means for detecting a contour image in an image obtained by the photographing means as a thread part forming the grain fabric, and the detected thread part Image analysis means for acquiring the direction of the texture, and information processing means for calculating the distribution of a plurality of yarn portions in the acquired direction, wherein the direction distribution obtained by the information processing means is used to measure the crimp standing of the crimped fabric. An apparatus for measuring the crimping property of a crimped fabric, which is a result. 2. The apparatus according to claim 1, wherein the image analyzing unit performs a thinning process on the contour image detected by the yarn portion detecting unit, and then executes the yarn processing. An apparatus for measuring the crimp standing property of a crimped fabric, which acquires a direction of a portion. 3. The texture measuring device according to claim 1, wherein the information processing means further converts the value of the directional distribution into a frequency. 4. A thread portion detecting step of detecting an outline image from among images of the grain fabric as a thread portion forming the grain fabric by an image analysis device, and detecting a direction of the detected thread portion by the image analysis device. Acquiring an image analysis step, comprising an information processing step of calculating the distribution of the plurality of yarn portions in the acquired direction by the image analysis device,
A method for measuring the crimp standing property of a crimped fabric, wherein the direction distribution obtained by the information processing step is used as a measurement result of the crimp standing property of the crimped fabric. 5. The method according to claim 4, wherein in the image analysis step, after performing a thinning process on the contour image detected by the yarn portion detecting means, the yarn is removed. A method for measuring the crimping property of a crimped woven fabric, comprising acquiring a direction of a portion. 6. The method according to claim 4, wherein the value of the direction distribution is further converted to a frequency in the information processing step.