JP2000251084A - Device and method for extracting contour and program recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a device and a method for extracting contour capable of obtaining an exact contour curve by obtaining an exact color shading axis. SOLUTION: When any representative point is designated from a user, an update block extracting part 31 extracts the update block of a curve and obtains a representative point 1 and a representative point 2 sandwiching the update block neither too much nor too little. On the basis of the representative point 1, the representative point 2 and an image, an optimum color shading axis calculating part 32 obtains a color space shading axis to maximize the contrast around an edge in the update block. In a contour curve generating part 33, a new contour curve in the update block is generated from the image, the representative point 1, the representative point 2 and the color shading axis. In an update block synthesizing part 34, the contour curve in the updated block is synthesized with a closed curve and generated as a new closed contour curve. With the movement/addition/deletion of the representative point due to the user, while updating occurs, the closed contour curve is continuously updated as well.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a contour extracting apparatus and method for extracting a contour of an object of interest from an image, and a program recording medium for recording a program to which the contour extracting method is applied.

[0002]

2. Description of the Related Art Soft keys are used to extract an image of an object of interest from an image and combine the extracted object image with another image. The key generation device generally includes a contour closed curve generation unit, a both-end closed curve generation unit, and a soft key generation unit. From the contour closed curve generated by the contour closed curve generation unit, the double-ended closed curve generation unit generates a double-ended closed curve, and the soft key generation unit generates the soft key using the double-ended closed curve.

[0003] In the contour closed curve generation unit, when a user designates a representative point on an edge of an image using a two-dimensional pointing device such as a mouse or a tablet (not shown) as an input means, the coordinates of the representative point on the edge are calculated. ,
A color space projection axis that maximizes the contrast around the edge in the update section is determined, a new contour curve in the update section is generated based on the color projection axis and the like, and a new closed contour curve is generated from the new contour curve.

Here, a specific conventional method for generating the color projection axis will be described with reference to FIG.

In general, the color distribution Cf of the foreground area around the edge
It is known that the color distribution Cb of the background region and the background region have a banana shape extending in the luminance axis direction as shown in FIG. For this reason, conventionally, the axis Axis1 in the luminance axis direction shown in FIG. 21 has been used as the color projection axis.

[0006]

The above-mentioned FIG.
In the method described above, the color distribution Cf of the foreground area is projected in the range of Wf1. On the other hand, the color distribution Cb of the background area is Wb
1 is projected to the area. In this case, the color change in each area of Cf and Cb is large, and the color change between Cf and Cb is small. Since the color change in the edge area of the image is a color change between Cf and Cb, Axis1 is not of good quality as a color projection axis. Therefore, the new contour curve in the update section generated using this color projection axis is also of poor quality, and it is not possible to generate an accurate soft key.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and has as its object to provide a contour extracting apparatus and method capable of finding an accurate contour curve by finding an accurate color projection axis.

[0008]

According to the present invention, there is provided a contour extracting apparatus for extracting a contour of an object from an image, the method comprising extracting a representative point on an edge of the object. Update interval extracting means for obtaining a set of representative points sandwiching the update interval from the coordinates and the initial closed curve; and a set of representative points obtained by the update interval extractor and the contrast around the edge in the update interval from the image. A color projection axis calculation means for finding a color projection axis to be maximized; a set of representative points obtained by the color projection axis calculation means and the update section extraction means obtained by the color projection axis calculation means; And a closed contour curve synthesizing means for generating a new closed contour curve by synthesizing the closed contour curve in the update section generated by the contour curve generating means.

In order to solve the above-mentioned problems, a contour extraction method according to the present invention is a contour extraction method for extracting a contour of an object from an image. An update section extraction step for obtaining a set of representative points sandwiching the update section from the closed curve; and a color for maximizing the contrast around the edge in the update section from the set of representative points obtained in the update section extraction step and the image. A color projection axis calculation step for obtaining a projection axis, a set of representative points obtained in the color projection axis calculation step and the update section extraction step obtained in the color projection axis calculation step, and a contour curve in an update section from the image. The method includes a contour curve generating step of generating the contour curve, and a contour closed curve synthesizing step of generating a new contour closed curve by combining the contour curve in the update section generated in the contour curve generating step with a closed curve.

In order to solve the above-mentioned problems, a program recording medium according to the present invention is a program recording medium for recording a contour extraction program for extracting a contour of an object from an image. An update interval extraction step for obtaining a set of representative points sandwiching the update interval from the coordinates of the upper representative point and the initial closed curve, and an edge in the update interval from the set of representative points obtained in the update interval extraction step and the image A color projection axis calculation step for obtaining a color projection axis for maximizing the surrounding contrast; a color projection axis obtained in the color projection axis calculation step; a set of representative points obtained in the update section extraction step; A contour curve generating step of generating a contour curve in the update section from the above, and combining the contour curve in the update section generated in the contour curve generating step with a closed curve to generate a new contour closed curve And storing a program and a Guo closed curve synthesis step.

Therefore, according to the present invention, the color projection axis calculation means and the process provide the color projection which maximizes the contrast around the edge in the update interval from the set of representative points and the image obtained by the update interval extraction means and the process. The axis can be determined.

[0012]

Embodiments of the present invention will be described below with reference to the drawings. This embodiment is a key generation device shown in FIG. 1, which generates a soft key based on a contour area extracted using the contour extraction device according to the present invention.

From the closed contour curve obtained by the closed contour curve generating section 21, a double ended closed curve generating section 22 generates a double ended closed curve,
The soft key generation unit 23 generates a key image from the closed curve at both ends.

The contour closed curve generating section 21 is a specific example of the contour extracting device according to the present invention, and quickly generates a contour closed curve according to a user's request in accordance with a simple operation by the user.

FIG. 2 shows a detailed configuration of the contour closed curve generation unit 21. The contour closed curve generator 21 includes an update section extractor 31, an optimum color projection axis calculator 32, a contour curve generator 33, and an update section synthesizer 34.

When the representative point is designated by the user, the update section extracting section 31 extracts the update section of the curve, and obtains the representative points 1 and 2 that sandwich the update section without excess or deficiency. Specifically, when the user specifies a representative point on the edge of the image using a two-dimensional pointing device such as a mouse or a tablet (not shown) as an input unit, the coordinates of the representative point on the edge are supplied to the update section extracting unit 31. . In addition, for example, a closed curve such as a circle, a square, or a polygon is also provided to the update section extraction unit 31 as an initial shape. The update section extraction unit 31 uses the coordinates of the representative points on the edge and the initial shape.
Finds representative points 1 and 2 that sandwich the update section without excess or deficiency.

The optimum color projection axis calculation unit 32 determines a color space projection axis that maximizes the contrast around the edge in the update section based on the representative point 1 and the representative point 2 and the image. The details of the optimum color projection axis calculation unit 32 will be described later.

The contour curve generator 33 generates a new contour curve in the update section from the image, the representative point 1, the representative point 2, and the color projection axis. The details of the contour curve generation unit 33 will also be described later.

The updated section synthesizing section 34 combines the contour curve of the updated section with a closed curve to generate a new closed contour curve. While the update occurs due to the movement, addition, or deletion of the representative point by the user, the contour closed curve is also updated.

FIG. 3 shows a specific example of the contour closed curve generated by the update section synthesizing section 34. That is, the contour closed curve is shown in FIG.
As shown in (1), it is composed of a representative point P on the edge for which the user directly designates coordinates, and a spline curve L passing through the representative point P and passing on the edge.

FIG. 4 is a detailed diagram of the optimum color projection axis calculation unit 32. The optimum color projection axis calculation unit 32 calculates a neighborhood optimum color projection axis in the vicinity area of the representative point 1 and the representative point 2, and calculates an optimum color projection axis calculation unit 41 near the representative point and an optimum color projection axis calculation unit near the representative point 41, and a color projection axis synthesizing section 42 for synthesizing the color projection axis using the color projection axis 1 and the color projection axis 2 from the two calculation sections 41, 41.

In the optimum color projection axis calculation unit 41 near the representative point,
A neighborhood optimum color projection axis that maximizes the contrast around the edge included in the neighborhood area of the representative point is obtained. Now, it is assumed that a representative point 1 (p0) and a representative point 2 (p1) are obtained as shown in FIG. At this time, the representative point color projection axis calculation unit 41 calculates the color projection axis (1) B0 at which the contrast is maximum among the edges included in the vicinity area A1 of the representative point p0. Further, the color projection axis calculation unit 41 near the representative point
Is an edge included in the area A2 near the representative point p1,
The color projection axis (2) B1 at which the contrast becomes maximum is obtained by calculation. The detailed configuration of the color projection axis calculation unit 41 near the representative point will be described later.

The color projection axis synthesizing section 42 synthesizes the neighborhood optimum color projection axis (1) B0 and the neighborhood optimum color projection axis (2) B1 separately obtained in the vicinity area of the representative points 1 and 2, and updates them. One color projection axis that maximizes the contrast of the edge of the section is determined. The combining method here may use, for example, the average vector of the color projection axes as the combined axis. However, in this case, when the vectors of the two color projection axes form an obtuse angle, it should be noted that the description will be made with reference to FIG. 6 below.

As shown in FIG. 6A, the color projection axis vectors obtained at the representative points on the above-mentioned edges at both ends of the update section are defined as v0 and v1. At this time, assuming that a composite vector c of v0 and v1 defined by the following equation is a color projection axis of the section, this c is substantially perpendicular to both v0 and v1, and the color projection axis of the section is Not suitable as an axis.

C = v0 + v1 This is because v0 and v1 form an obtuse angle. In the case of an obtuse angle, that is, when the inner product v0 · v1 is negative, FIG.
As shown in (B), for one of the vectors, for example, v0 'and v1 obtained by inverting v0, a combined vector c' is obtained as in the following equation, and is used as a color projection axis.

V0 '=-v0 c' = v0 '+ v1 As a result, an axis nearly horizontal to both v0 and v1 can be obtained.

Next, although the order is reversed, the detailed configuration of the above-described representative point vicinity color projection axis calculation unit 41 will be described with reference to FIG. The optimal color projection axis calculation unit 41 near the representative point includes a straight edge detection unit 51 and a color information acquisition unit 52 around the edge.
And a color projection axis calculation unit 53.

For example, the straight-line edge detection unit 51 in the optimum color projection axis calculation unit 41 near the representative point, which calculates the color projection axis near the representative point 1, calculates the image, the representative point 1 and the adjacent point (neighboring representative). Based on the point 2), the representative point 1 (p
A linear edge component included in the neighborhood A0 of (0) is detected, and an equation of the straight line is obtained. When a plurality of straight edges are included in the image of the vicinity area A0, for example, the one having the strongest edge is adopted.

The optimum color projection axis calculation unit 41 in the vicinity of the representative point for calculating the color projection axis near the representative point 2 is as follows.
The straight-line edge detection unit 51 calculates a linear edge component included in the neighborhood A1 of the representative point 2 (p1) shown in FIG. 5 based on the image, the representative point 2, and the adjacent point (neighboring representative point 1). Is detected, and the equation of the straight line is obtained. Here, if a plurality of straight edges are included in the image of the neighboring area A1, for example, the one with the strongest edge is adopted.

More specifically, the operation principle and the detailed configuration of the linear edge detecting section 51 will be described below with reference to FIGS.

FIG. 8 shows a representative point (anchor point) p0.
Shows a slight deviation from the edge of the image. Since the representative point is often placed off the edge as described above, it is necessary to improve the operability.
In such a case, it is necessary to estimate the position and direction of the edge.

Further, in FIG. 8, the edge near the representative point p0 is not uniquely determined, and a plurality of edge candidates such as E1 and E2 may exist. For this reason, the straight edge detection unit 51
Is not originally one, but is naturally a list of straight lines ordered by priority.

Next, in a local area near the representative point, attention is paid to the fact that edges are more linear.
An estimation method for estimating the position and direction of an edge using the Hough transform will be described with reference to FIG.

As shown in FIG. 9A, when a linear edge exists near a representative point (anchor point),
The gradient direction at the pixels on the edge is perpendicular to the edge. Assuming that the angle in the gradient direction is θ and the signed distance between the edge and the anchor point is ρ, all the pixels existing on the same edge have θ and ρ which are close to each other. It concentrates on the local area as shown in FIG.

Using this, a two-dimensional histogram in the θ, ρ space is created, and a linear part is detected using the frequency.

FIG. 10 shows a detailed configuration of the straight edge detecting section 51. First, the nearby area cutout unit 81 generates a partial image obtained by cutting out a local area near an anchor point.

The monochrome image generation section 82 generates a monochrome image projected on a certain appropriate color projection axis, for example, a luminance axis. Here, since it is used as a rough estimate, it does not need to be the optimal axis.

The gradient image generation unit 83 generates a gradient image by applying a Sobel filter or the like to a monochrome image.

The ρ · θ two-dimensional histogram generator 84 calculates ρ · θ for all the pixels of the gradient image to generate a histogram. Assuming that the anchor point is the origin and the gradient vector at a certain pixel P (x, y) is (gx, gy), ρ, θ is ρ = − (gx · x + gy · y) / sqrt (gx ＾ 2 +
gy ＾ 2) θ = arctan (gy / gx). Here, gx> 0, and sqrt represents a square root.

The priority generation unit 85 assigns a priority using the frequency of the histogram, the value of ρ, the direction to the adjacent anchor point, and the like.

The linear equation coefficient calculator 86 calculates the coefficients of the linear equation based on the values of θ · ρ. Ax is a straight line equation
If + bx + c = 0, then a = cos θ b = sin θ c = −ρ.

As described above, the straight edge detecting unit 51
A straight line equation can be obtained, and the obtained straight line equation is sent to the edge surrounding color information acquisition unit 52. As described with reference to FIG. 8, when the edge near the representative point p0 is not uniquely determined and a plurality of edge candidates may exist,
The output of the straight line edge detection unit 51 is not one, but it is natural to output a list of straight lines ordered according to the priority.

Next, the edge surrounding color information acquisition section 52 shown in FIG.
Then, the periphery of the linear equation (edge) detected by the edge detection unit 51 is sampled, and a histogram of the color distribution classified into one side and the other side of the edge is generated. Specifically, there is a method of acquiring a color within a region of a diameter and several pixels at a position at a certain fixed distance from a straight line. FIG. 1 shows the operation of the edge surrounding color information acquisition unit 52 by this method.
1 will be described.

As shown in FIG. 11, it is assumed that a straight line L approximating the edge is placed on the edge of the image. At this time, a circle having a radius r having a center Q0 and a center Q1 is placed at a position passing through a point P on L and perpendicularly to the straight line by a distance h, and samples colors in this area. This allows
In the vicinity of the point P, color information around the edge can be obtained.

Returning to FIG. 7, the color projection axis calculation unit 53 calculates the color distribution histogram of the edge surrounding color information acquisition unit 52 from the color distribution histogram.
Find a color projection axis that maximizes edge contrast.
For example, there is a method in which a vector connecting the centers of gravity of distributions on one side and the other side of an edge in a color space is used as an axis.

The operation of calculating the color projection axis in the color projection axis calculation section 53 will be described below with reference to FIG.

The color distribution around the edge is generally shown in FIG.
It is known to form a banana extending in the direction of the luminance axis as shown in FIGS.

At this time, assuming that the axis Axis1 in the luminance axis direction is the color projection axis as shown in FIG. 12A, the color distribution Cf of the foreground area is projected in the range of Wf1. On the other hand, the color distribution Cb of the background area is projected in the range of Wb1. In this,
The color change in each area of Cf and Cb is large,
The color change between Cb is small. Since the color change in the edge region of the image is a color change between Cf and Cb, Axis1 is not the color projection axis to be obtained.

As shown in FIG. 12B, when an axis Axis2 substantially perpendicular to the luminance axis direction is used as the color projection axis, Cf becomes Wf
2. Since Cb is projected onto Wb2, the color change in each area of Cf and Cb is small, and the color change between Cf and Cb is large, so that it is close to the desired color projection axis.

Hereinafter, this is formulated. Assuming that the color projection axis vector is a, the sum of the class sum of squares matrices in each of the color distributions Cf and Cb is Qw, and the class sum of squares matrix between the color distributions Cf and Cb is Qb, the class dispersion of Cf and Cb is aTQw
The interclass dispersion between a, Cf and Cb is aTQba. Here, aT represents transposition of a.

The color projection axis calculation unit 53 obtains the axis a for increasing the ratio of the interclass dispersion to the intraclass dispersion as much as possible.

The average of Cf is F ^* , the average of Cb is B ^* , Qw
The above a is represented by a = Iw (F ^* -B ^* ), where Iw is an inverse matrix of Iw. This is used as a color projection axis.

The above is a detailed description of a specific example of the optimum color projection axis calculation unit 32 in FIG. Further, the optimum color projection axis calculation unit 32 may calculate the optimum color projection axis by the method shown in FIG.

Assume that an anchor point p0 and an adjacent anchor point p1 are located on the edge of the image as shown in FIG. At this time, since the edge may be largely off the line segment connecting p0 and p1, the edge is placed at equal intervals, for example, at intervals of L / 4 with respect to the line segment length L on the line segment p0p1. For each of the points q0, q1, and q2, a search is made for an area having the largest color change in the range of the length H on a line segment perpendicular to p0p1.

Assuming that the color at a certain point r is C (r), the color change vector is dC / dr and its magnitude is | dC
/ Dr |. The value r at which this value becomes the maximum value is obtained.

As a result of the search, as shown in FIG.
It is assumed that r1 and r2 have been obtained. At this time, r0, r
The color change vector dC / dr is determined for each of the color difference vectors 1 and r2, and the average value is set as the optimal color projection axis.

The color change vector may be obtained as follows. In the case of r0, on a straight line perpendicular to the line segment p0p1, a point s having r0 as a center and separated from each other by a distance width h.
For 00 and s01, colors C (s00) and C (s01)
And the difference vector ΔC = C (s01) −C (s
00) is substituted for the color change vector. The same applies to r1 and r2.

Next, details of the contour curve generator 33 in FIG. 2 will be described with reference to FIG. The contour curve generation unit 33 includes a high contrast monochrome image generation unit 6
1, a gradient vector field generation unit 62, a minimum cost path search unit 63, and a spline curve generation unit 64.

High-contrast monochrome image generator 61
Then, a monochrome image is generated by projecting the color at each pixel of the image and the input color projection axis.

The gradient vector field generation unit 62 generates a two-dimensional XY gradient vector field by applying a gradient detection operator to a monochrome image.

The minimum cost path search unit 63 determines a part having a strong edge in the gradient vector field as a low cost part, and obtains a discrete pixel string representing a path that minimizes the accumulated cost. The spline curve generation unit 64 generates a smooth spline curve from the pixel sequence.

Then, as described above, the update section synthesizing section 34 synthesizes the contour curve of the updated section into a closed curve and generates a new contour closed curve. While the update occurs due to the movement, addition, or deletion of the representative point by the user, the contour closed curve is also updated.

The above is the details of the closed contour generating section 21 in FIG. 1 for generating the closed contour. In the contour closed curve generation unit 21, since the optimum color projection axis that maximizes the edge contrast can be obtained in the optimum color projection axis calculation unit 32, an accurate contour curve can be obtained. Therefore, the key generation device including the contour closed curve generation unit 21 can generate an accurate soft key.

The above-described key generation device using the closed contour generating unit 21 (the configuration is the same as the key generating device shown in FIG. 1) as described above, And a closed-end curve generator 2 for generating a closed-end curve from an image as shown in FIG.
2 and a soft key generation unit 23 for generating a key image from the both-end closed curve generated by the both-end closed curve generation unit 22.

The closed contour generating section 22 generates a closed-end curve from the closed contour. Specifically, the present applicant generates a closed-ended curve using the “contour extraction method” disclosed in Japanese Patent Application Laid-Open No. 10-164436.

This “contour extraction method” determines a contour area for the contour of the object, calculates a gradient vector in the contour area, and, based on the gradient vector in the contour area, moves along the edge of the edge along the edge of the contour area. And a plurality of boundary positions on the outside are extracted, and boundary coordinate information representing the respective boundary positions is generated for each of the inside and outside of the edge, and two boundary curves approximating each shape represented by each boundary coordinate information are obtained. It is generated as a closed curve at both ends of the object.

Further, the contour closed curve generation unit 22 is provided with both ends which have been deformed into a shape reflecting the width / offset value by the curve deformation technique disclosed in the specification and drawings of Japanese Patent Application No. 10-268687 filed by the present applicant. A closed curve may be generated.

This curve deformation technique converts two curves representing the inner and outer boundary positions in the outline of the object included in the image into a series of points, generates a series of points for each curve, and The coordinates of each point are changed by linking a series of points on the curve, and two curves, that is, closed contours at both ends are reconstructed from the coordinates of each point whose coordinates have been changed.

The soft key generation unit 23 generates a three-dimensional curved surface to which the α axis of the key signal is added based on the both-end curve generated by the both-end closed curve generation unit 22, and the area between the both-end curves has an α value of Generate a soft key image that changes smoothly.

However, in the key generator using the contour closed curve generator 21 for generating one closed contour curve described above, only one output for one type of input is provided in each stage of data processing. Therefore, when the edge representative points at both ends are determined, the contour curve in that section is uniquely determined. If the unique result does not match the user's subjectivity, the only option is to change the position, add, or delete the edge representative point.

For example, taking the color projection axis calculation unit 41 near the representative point shown in FIG. 7 as an example, the straight line obtained by the straight line edge detection unit 51 has only one strongest edge. Originally, as described with reference to FIGS. 8 and 10, a plurality of evaluation values are obtained.

Therefore, the contour closed curve generation unit 21 shown in FIG.
Based on the principle shown in FIG. 5, the configuration shown in FIG. 2 is changed to the closed contour generating section 21 'having the configuration shown in FIG. 16, and a plurality of candidates are presented to the user so that the user's selection is used as an auxiliary input. .

The contour closed curve generator 21 ′ conceptually includes a data processor 10, a data converter 11, a display device 12,
An operation device 13 and an output data selection unit 14 are provided.

The data processing unit 10 processes the input data
A plurality of output data candidate lists are presented by applying a plurality of algorithms and parameters. The data conversion unit 11 generates a candidate list of data that can be subjectively evaluated by humans from the candidate list. This candidate list is displayed on the display device 12.
Displayed above.

When the user selects a desired candidate using the operating device 13 while looking at the display device 12, the number of the selected candidate is sent to the output data selecting section 14, and the output data selecting section 14 The output data as desired is sent to the display device 12 again. As a result, the user can obtain an expected result.

As shown in FIG. 16, the contour closed curve generator 21 'includes an update section extractor 31, a contour curve generator 33, and an update section synthesizer 34 having the same configuration as that shown in FIG.
In addition, a candidate selection function addition / change portion surrounded by a broken line is provided.

The candidate selection function addition / change portion includes a color projection axis candidate calculation section 32 'for calculating a plurality of color projection axes, and a contour curve for generating a contour curve candidate list corresponding to the plurality of color projection axis candidate lists. It includes a generation unit 33 and a candidate list selection unit 71 that displays the contour curve candidate list generated by the contour curve generation unit 33 on the display device 12 as shown in FIG. Candidate list selection unit 71
Represents the color projection axis selected by the user as the contour curve generator 3
Send to 3.

FIG. 17 shows the detailed configuration of the color projection axis candidate calculation unit 32 '. The color projection axis candidate calculation unit 32 ′ calculates the representative point 1
A representative point neighboring optimum projection axis candidate calculating unit 41 ′ and a representative point neighboring optimum projecting axis candidate calculating unit 41 ′ for calculating a plurality of candidates for the nearest optimum color projection axis of the representative point 2; It comprises a color projection axis synthesis candidate generation unit 42 'for generating a color projection axis synthesis candidate using the color projection axis candidate list 1 and the color projection axis candidate list 2 from 41'. If there are n candidates in the list 1 of color projection axis candidates from the two calculation units 41 ′ and 41 ′ and there are m candidates in the list 2 of color projection axis candidates, the color projection axis synthesis candidate generation unit 42 ′ generates a list of n × m candidates.

Optimum projection axis candidate calculation unit 41 ′ near a representative point
Outputs a list of a plurality of color projection axis candidates by a linear equation.

FIG. 18 shows the detailed configuration of the above-mentioned optimal projection axis candidate calculating unit 41 'near the representative point. The representative point neighborhood optimal projection axis candidate calculation unit 41 ′ includes a straight edge candidate detection unit 51 ′.
And the color information acquisition unit 52 around the edge and the color projection axis calculation unit 5
3

For example, a candidate color projection axis candidate calculation unit 41 ′ for calculating a color projection axis candidate in the vicinity of the representative point 1 is obtained.
The internal straight edge candidate detection unit 51 'is included in the vicinity area A0 of the representative point 1 (p0) shown in FIG. 5 based on the image, the representative point 1, and the adjacent point (adjacent representative point 2). A plurality of linear edge components are detected, a straight line equation is obtained, and a list of a plurality of straight line equation candidates is generated.

Further, a candidate for a color projection axis near the representative point 2 by calculation, a candidate for a straight edge candidate 51 ′ inside the candidate for color projection axis candidate calculation unit 41 ′ near the representative point,
And a plurality of linear edge components included in the vicinity area A1 of the representative point 2 (p1) shown in FIG. 5 based on and the adjacent point (neighboring representative point 1), and an equation of the straight line is obtained. Generate a list of candidate linear equations.

The color information acquisition section 52 around the edge and the color projection axis calculation section 53 also output a list of a plurality of candidates.

For this reason, the color projection axis candidate calculation section 32 ′ in the contour closed curve generation section 21 ′ shown in FIG. 17 converts the color projection axis candidate list into the contour curve generation section 33 and the candidate list selection section in FIG. It can be sent to the unit 71.

The contour curve generator 33 has the same configuration as that shown in FIG. 14, but generates a plurality of contour curve candidate lists corresponding to the color projection axis candidate lists and displays them on the display device. That is, the contour curve generation unit 33 converts the plurality of color projection axis candidates into data that can be subjectively evaluated by the user, and displays, for example, the plurality of contour curves on the display device 12 shown in FIG. . Alternatively, a plurality of contour curves may be displayed in an overlapping manner, or may be displayed at once using a plurality of windows.

The user can select a desired contour curve from the plurality of contour curves displayed on the display device 12. The user's selection result is input to the candidate list selection unit 71. The candidate list selection unit 71 selects a color projection axis that forms a contour curve on the display device 12 selected by the user from the candidate list, and sends the color projection axis to the contour curve generation unit 33 that originally forms the contour closed curve generation unit 21 ′. Supply.

The contour curve generator 33 is provided with the candidate list selector 7.
The contour curve is calculated based on the color projection axis selected in step 1 and supplied to the update section synthesis unit 34.

As described above, the update section synthesizing unit 34
The contour curve of the updated section is combined with a closed curve to generate a new contour closed curve. Moving representative points by user
While the update occurs due to addition or deletion, the contour closed curve is also updated.

The outline closed curve generator 21 'has been described above. The contour closed curve generation unit 21 'constitutes the key generation device shown in FIG.
Used instead of

The operation of the key generation device in this case will be described with reference to FIG.

After the representative points p1 and p2 on the edge are designated by the user, the paths c1 and c2 are used as candidate contours in FIG.
The information is presented on the display device 12 as shown in FIG. FIG.
9 (B) shows a state in which the mouse cursor has been moved to the vicinity of c1 because the user selects c1. When the user performs a click operation, FIG.
As shown in (C), c1 is determined.

In the existing method, if the expected contour curve cannot be obtained, there is no other method than to change, add, or delete the position of the edge representative point. On the other hand, in the above-described key generation device whose operation has been described with reference to FIG. 19, the operation for obtaining the expected contour curve is a one-step operation of clicking once on the desired contour. It can be seen that the operation for obtaining the desired contour curve can be reduced.

Further, in the above-described key generation device, the contour extraction device of the present invention is implemented by hardware in terms of the contour closed curve generation unit 21 '.
However, the contour extraction method of the present invention may be realized by a software program and processed by, for example, a computer system as shown in FIG.

This computer system comprises an arithmetic processing unit 1, a program memory 2, a data memory 3, a frame memory 4, an image display device 5, an input device 6, and an external storage device 7 connected to a bus 8.

The program memory 2 stores the above-described contour extraction method as a software program. The arithmetic processing unit 1 sequentially retrieves the software program from the program memory 2 and executes it. Data memory 3
Stores data that is being processed by the arithmetic processing unit 1.

The frame memory 4 stores the image data obtained by the arithmetic processing unit 1 executing the software program and using the data memory 3 for image display. The image data stored in the frame memory 4 is displayed on the image display device 5 and can be viewed by the user. The image display device 5 can perform multi-window display, and can simultaneously display a plurality of images.

The input device 6 uses, for example, a mouse or a keyboard, and data is input by the user. The external storage device 7 stores image data and the like. The bus 8 connects the above-described units, and moves program codes and data to and from each other.

The image data is stored in the data memory 3, and when the user inputs the coordinates of two points indicating the section for which the contour curve is to be obtained through the input device 6, the arithmetic processing device 1
In step (1), a candidate list of contour curves is obtained, imaged, and output to the image display device 5 through the frame memory 4.

On the basis of the candidates displayed on the image display device 5,
When the user inputs a contour curve that meets his / her expectation through the input device 6, the contour curve that best meets the user's expectation is stored in the data memory 3. The image data and the contour curve stored in the data memory 3 are formed into an image according to a user's instruction, and output to the image display device 5 through the frame memory 4. Note that the present invention is not limited to the case of edge detection,
A plurality of candidates can be output, and the present invention can be applied to all data processing that can be converted into data that can be subjectively evaluated.

[0100]

According to the present invention, the color projection axis calculating means and the process maximize the contrast around the edge in the updating interval from the set of representative points and the image obtained by the updating interval extracting means and the process. Since the color projection axis is obtained, an accurate contour curve can be obtained.

[Brief description of the drawings]

FIG. 1 is a block diagram of a key generation device according to an embodiment of the present invention.

FIG. 2 is a block diagram of a contour closed curve generation unit which is a specific example of the contour extraction device of the present invention applied to the key generation device.

FIG. 3 is a diagram showing a specific example of an outline closed curve generated by the outline closed curve generation unit shown in FIG. 2;

FIG. 4 is a block diagram showing a detailed configuration of an optimum color projection axis calculation unit that forms the contour closed curve generation unit shown in FIG. 2;

FIG. 5 is a diagram for explaining the operation principle of the optimum color projection axis calculation unit near the representative point, which constitutes the optimum color projection axis calculation unit shown in FIG. 4;

FIG. 6 is a diagram for explaining an operation principle of a color projection axis synthesizing unit constituting the optimum color projection axis calculating unit shown in FIG. 4;

FIG. 7 is a block diagram showing a configuration of an optimum color projection axis calculation unit near a representative point, which constitutes the optimum color projection axis calculation unit shown in FIG. 4;

FIG. 8 is a diagram for explaining the operation principle of a straight-line edge detection unit constituting the optimum color projection axis calculation unit near the representative point shown in FIG. 7;

FIG. 9 is a diagram for explaining the operation principle of an estimation method of estimating the position and direction of an edge by a straight-line edge detector constituting the optimal color projection axis calculator near the representative point shown in FIG.

FIG. 10 is a block diagram showing a configuration of a straight-line edge detection unit constituting the optimum color projection axis calculation unit near the representative point shown in FIG. 7;

FIG. 11 is a diagram for explaining the operation principle of a color information acquisition unit around an edge, which constitutes the optimal color projection axis calculation unit near the representative point shown in FIG. 7;

FIG. 12 is a diagram for explaining the principle of operation of the color projection axis calculation unit constituting the optimum color projection axis calculation unit near the representative point shown in FIG. 7;

FIG. 13 is a diagram for explaining another principle of operation of the optimum color projection axis calculator, which constitutes the contour closed curve generator shown in FIG. 2;

FIG. 14 is a block diagram illustrating a configuration of a contour curve generation unit included in the contour closed curve generation unit illustrated in FIG. 2;

FIG. 15 is a diagram for explaining a conceptual principle for making the contour closed curve generation unit a contour closed curve generation unit that presents a plurality of contour curve candidates for selection by a user.

FIG. 16 is a block diagram illustrating a configuration of a contour closed curve generation unit whose principle has been described with reference to FIG. 15;

FIG. 17 is a block diagram of a color projection axis calculation unit included in the closed contour curve generation unit shown in FIG. 16;

FIG. 18 is a block diagram of an optimum color projection axis candidate calculation unit near a representative point, which constitutes the color projection axis calculation unit shown in FIG. 17;

FIG. 19 is a diagram for explaining the operation of the key generation device having the closed contour generation unit shown in FIG. 14;

FIG. 20 is a block diagram of a computer system that uses the contour extraction method of the present invention as a software program.

FIG. 21 is a diagram for explaining a specific conventional method of generating a color projection axis.

[Explanation of symbols]

21 contour curve generator, 31 update section extractor, 32
Optimal color projection axis calculation unit, 33 contour curve generation unit, 34 update section synthesis unit, 41 optimal color projection axis calculation unit near the representative point,
42 color projection axis synthesis unit, 51 straight edge detection unit, 52
Color information acquisition unit around the edge, 53 color projection axis calculation unit

Claims (20)

[Claims] 1. A contour extraction device for extracting a contour of an object from an image, wherein an update section extracting means for obtaining a set of representative points sandwiching the update section from coordinates of a representative point on an edge of the object and an initial closed curve. A color projection axis calculation means for obtaining a color projection axis that maximizes the contrast around an edge in the update section from the set of representative points obtained by the update section extraction means and the image; and the color projection axis calculation means A contour curve generating means for generating a contour curve in an update section from the set of representative points obtained by the color projection axis determined in the above, the update section extracting means and the image, and a contour curve generated by the contour curve generating means. A contour extraction device comprising: a contour closed curve synthesizing unit that combines a contour curve in an update section with a closed curve to generate a new contour closed curve. 2. The color projection axis calculation means, comprising: an optimum color projection axis calculation means for calculating an optimum color projection axis in a vicinity area of each of the set of representative points; And a color projection axis synthesizing means for synthesizing a color projection axis that maximizes contrast around an edge in the update interval using the two optimal color projection axes calculated by the projection axis calculation means. The contour extraction device according to claim 1. 3. The optimum color projection axis calculating means in the neighboring area includes a straight edge detecting means for detecting a linear edge component based on the image and the representative point in each of the neighboring areas; Color information obtaining means for obtaining color information around a linear edge component detected by the means, and color projection for obtaining a color projection axis for maximizing edge contrast from the color information obtained by the color information obtaining means. 3. The contour extracting device according to claim 2, further comprising an axis calculating unit. 4. A straight-line edge detecting means for generating a partial image of a local area near a representative point from the image and the representative point, and a monochrome image of the partial image cut by the local-area cutting means. A monochrome image generating unit, a gradient image generating unit that generates a gradient image from the monochrome image generated by the monochrome image generating unit, and a gradient direction angle θ from the gradient image generated by the gradient image generating unit. A two-dimensional histogram generating means for generating a two-dimensional histogram of a signed distance ρ between the edge and the representative point; an angle θ generated by the two-dimensional histogram generating means;
Priority generating means for prioritizing the signed distance ρ, and the angles θ, which are prioritized by the priority generating means,
4. The contour extracting device according to claim 3, further comprising: a straight line equation coefficient calculating unit for calculating a coefficient of a straight line equation of the straight edge based on the value of the signed distance ρ. 5. The color information obtaining means samples the periphery of the linear edge component detected by the straight edge detection means and generates a histogram of color distribution classified into one side and the other side of the edge. 4. The contour extraction device according to claim 3, wherein: 6. The color information acquisition means, when a straight line approximating the edge is placed on the edge of the image, passes through a point on the straight line, and is positioned on both sides separated by a predetermined distance in a direction perpendicular to the straight line. 6. A method according to claim 5, further comprising: placing two circles having the same radius in the circle, and sampling colors in the area of the circle.
The contour extraction device as described. 7. The color projection axis calculation means calculates, as a color projection axis, a vector connecting the centers of gravity of the distributions on one side and the other side of the edge in the color space of the color distribution information acquired by the color information acquisition means. The contour extracting device according to claim 3, wherein 8. The color projection axis calculation means calculates the ratio of the intra-class variance and the inter-class variance of the distribution on one side and the other side of the edge in the color space of the color distribution information obtained by the color information obtaining means. 4. The contour extracting device according to claim 3, wherein the axis to be maximized is calculated as a color projection axis. 9. The color projection axis calculation means, for each of a plurality of equally spaced points on a line segment connecting a set of representative points placed on the edge of the image, perpendicular to the line segment. 2. The contour extraction according to claim 1, wherein a region having the largest color change is searched for on a vertical line segment drawn on both sides of the line segment by a predetermined length in a predetermined direction, and the color projection axis is obtained by calculation. apparatus. 10. The color projection axis calculation means obtains a color change vector on the vertical line segment, obtains a color change maximum point having the maximum size, and calculates the color change vector from the average of the color change maximum points. 10. The contour extraction device according to claim 9, wherein the projection axis is obtained by calculation. 11. A contour extraction method for extracting a contour of an object from an image, wherein an update section for obtaining a set of representative points sandwiching the update section from coordinates of a representative point on an edge of the object and an initial closed curve. An extraction step, a color projection axis calculation step of obtaining a color projection axis that maximizes the contrast around an edge in the update section from the set of representative points obtained in the update section extraction step and the image, and the color projection axis A contour curve generating step of generating a contour curve in an update section from the color projection axis determined in the calculation step, the set of representative points determined in the update section extraction step, and the image, and a contour curve generation step And synthesizing the contour curve in the updated section thus obtained into a closed curve to generate a new contour closed curve. 12. The color projection axis calculation step of calculating an optimum color projection axis in a neighborhood area of each of the set of representative points, the optimal color projection axis calculation step in the neighborhood area, A color projection axis synthesizing step of synthesizing a color projection axis that maximizes contrast around an edge in the update interval using the two optimal color projection axes calculated in the projection axis calculation step. The method for extracting a contour according to claim 11. 13. The optimal color projection axis calculating step in the neighboring area includes: a straight edge detecting step of detecting a linear edge component based on the image and the representative point in each of the neighboring areas; A color information obtaining step of obtaining color information around a linear edge component detected in the step, and a color projection obtaining a color projection axis that maximizes the edge contrast from the color information obtained in the color information obtaining step. 13. The contour extracting method according to claim 12, further comprising an axis calculating step. 14. The color information acquiring step includes sampling a periphery of the linear edge component detected in the linear edge detecting step to generate a histogram of color distribution classified into one side and the other side of the edge. Claim 1 characterized by the following:
3. The contour extraction method according to 3. 15. The color information obtaining step includes the steps of: when a straight line approximating an edge is placed on an edge of an image, passing through a point on the straight line and being separated from the straight line by a predetermined distance in the vertical direction. 15. The contour extraction method according to claim 14, wherein two circles having the same radius are placed on the circle, and colors in the area of the circle are sampled. 16. The color projection axis calculating step calculates a vector connecting the centers of gravity of the distributions on one side and the other side of the edge in the color space of the color distribution information obtained in the color information obtaining step as a color projection axis. 2. The method according to claim 1, wherein
3. The contour extraction method according to 3. 17. The color projection axis calculating step includes calculating a ratio between the intra-class variance and the inter-class variance of the distribution on one side and the other side of the edge in the color space of the color distribution information acquired in the color information acquiring step. 14. The contour extraction method according to claim 13, wherein an axis to be maximized is calculated as a color projection axis. 18. The color projection axis calculating step includes the steps of: calculating a vertical axis with respect to each of a plurality of equally spaced points on a line connecting a set of representative points placed on the edge of the image; 12. The contour extraction according to claim 11, wherein a region having the largest color change is searched for on a vertical line segment having a predetermined length drawn on both sides of the line segment in a predetermined direction, and the color projection axis is obtained by calculation. Method. 19. The color projection axis calculating step includes calculating a color change vector on the vertical line segment, obtaining a maximum color change point having the maximum value, and calculating the color change vector from the average of the maximum color change points. 19. The contour extraction method according to claim 18, wherein the projection axis is obtained by calculation. 20. A program recording medium which records a contour extraction program for extracting a contour of an object from an image, wherein an update interval is inserted from coordinates of a representative point on an edge of the object and an initial closed curve. An update interval extraction step for obtaining a set of representative points; and a color projection axis for obtaining a color projection axis for maximizing contrast around an edge in the update interval from the set of representative points obtained in the update interval extraction step and the image. A calculating step, a contour curve generating step of generating a contour curve in the update section from the image and the set of representative points determined in the color projection axis and the update section extraction step obtained in the color projection axis calculation step and the image. A program for synthesizing a contour curve in the update section generated in the contour curve generating step into a closed curve, and generating a new contour closed curve. Program recording medium characterized.