Method, device, computer program, computer system and machine-readable storage device for the representation and retrieval of the object in the image

 

The invention relates to the representation of the object appearing in the image. Its use in image processing, stored in a multimedia database, allows to provide the technical result in more accurate search objects in images. This technical result is achieved due to the fact that receive a scaled representation of the space of curvature (IPC) for the object outline by the smooth contour of the object, receive at least one additional parameter reflecting the distribution of the shape or mass of the smoothed version of the original curve, and connect the representation to the IPC and the additional parameter as a descriptor of the form object. This optional parameter may correspond to the eccentricity or the roundness of contour, the highest peak in the image in the IPC, it can be based on Fourier descriptors or Zernike moments, etc. 5 C. and 12 C.p. f-crystals, 3 ill.

The technical field to which the invention relates the Present invention relates to the representation of an object appearing in a still image or a video image, such as image, stored in a multimedia database, osobennyi In such applications, as a library of images or videos, it is desirable to have effective representation and storage of the contour or shape of objects or parts of objects that appear in still images or video images. A known method based on the shape index and search, uses a scaled representation of the space of curvature (IPC) (CSS). Details view of the IPC can be found in the article "Robust and Efficient Shape Indexing through Curvature Scale Space" (Sustainable and effective index of the form through the space with a curved scale) Proc. British Machine Vision conference, pp. 53-62, Edinburgh, UK, 1996, and "Indexing an Image Database by Shape Content using Curvature Scale Space" (Indexing databases of images via context forms through space with a curved scale) of the OEWG. IEE Colloquium on Intelligent Databases, London 1996, both written F. Mokhtarian, S. Abbasi, and J. Kittler, bibliographic details are provided here as a reference.

View the IPC uses a function of curvature for the path of the object, starting from an arbitrary point on the contour. This function of the curvature is studied as the shape of the path unfolds through a series of deformations, which smooth out the shape. Specifically, we calculate the zero crossing for the derivative of the function cigratte, known as the space is curved scale, where the x-axis represents the normalized arc length of the curve and the y axis is the expansion parameter, specifically, by setting the applied filter. The points on this graph form a loop response of the circuit. Each of the convex or concave part of the contour of the object corresponds to the loop in the image of the IPC. The coordinates of the most prominent peaks of the loops in the image of the IPC is used as a representation of the contour.

To search for objects stored in the database image that is consistent with the shape of the input object, we compute the representation of the IPC input object. The similarity between the input form and memorized forms is determined by comparing the position and the height of the peaks in the respective images of the IPC using the algorithm mates.

From the first of the above-mentioned article it is also known to use two additional parameters - roundness and eccentricity of the original form is to be excluded from the pairing process forms with significantly different parameters of roundness and eccentricity.

The problem with the view described above is that the search accuracy can sometimes be low, especially for curves to Puglia curves.

The object of the present invention is to introduce an additional tool description form for "contour shape of the prototype". This shape of the prototype is defined here as: 1) the original form, if the circuit has no convexity or concavity (i.e., for example, in the image of the IPC no peaks), or 2) the shape contour after smoothing is equivalent to the highest peak in the image of the IPC.

Note that the shape of the prototype is always convex.

For example, the shape of the prototype can be described by invariants, based on the moments of the area, as described in the article "Visual Pattern Recognition by Moments Invariants" (Visual pattern recognition by moment invariants, IEEE Transactions on Information Theory, Vol. IT-8, 179-187, 1962, written by M. K. No, the bibliographic data of which are given here as a reference, or by using Fourier descriptors, as described in the article "On Image Analysis by the Methods of Moments" On image analysis by the methods of moments, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 10, No. 4, July 1988, written Cho-Huak The bibliographic data of which are given here as a reference, or by using parameters such as eccentricity, roundness, etc., In the above-mentioned known methods eccentricity and army circuit prototype", which is different for curves having at least one peak of the IPC. Another difference is that in the known method, the eccentricity and circularity are used to exclude some forms of mates for finding similarity, as here, the applicant uses them (in addition to the peaks of the IPC) to get the value of the similarity measure. Finally, the applicant extends the additional parameters used in the pairing process, to the moment invariants, Fourier descriptors and Zernike moments.

As a result of implementation of the invention can be more accurate.

The invention is a Method of representing an object appearing in a still image or video image, by processing corresponding to the image signals, according to one object of the present invention, includes receiving a representation of the space with a curved scale (IPC) for the contour of the object by smoothing the contour of the object, receiving at least one additional parameter reflecting the distribution of the shape or mass of the smoothed version of the original curve, and link representation of the IPC and the additional parameter as a descriptor of the form object.

In the proposed method of attachment is ornately parameter may relate to a flattened contour, corresponding to the highest peak in the image of the IPC.

An additional parameter may correspond to the eccentricity of the path.

An additional parameter may correspond to the circularity of the contour.

At least one additional parameter can be used based on the view pane.

An additional parameter may be a torque invariant region.

An additional parameter may be based on Fourier descriptors.

An additional parameter may be based on Zernike moments for the area covered by the path.

Way to represent the set of objects appearing in a still image or video image, by processing signals corresponding to images, according to the second object of the invention contains, for each object, determining whether there is a significant change in the curvature in the contour of the object, and if the curvature in the contour of the object there are significant changes, then the descriptor form, and if the curvature in the contour of the object there are no significant changes, then the descriptor of the form, including at least said additional parameter reflecting the shape of the contour of the object.

acitelli changes in curvature, can be based on moment invariants areas, the Fourier descriptors or the Zernike moments of the contour.

Way of the search object in a still image or video image, by processing signals corresponding to images, according to the third object of the invention contains an introduction request in the form of a two-dimensional path, the receive descriptor mentioned circuit, the comparison of the mentioned query descriptor with each descriptor for a stored object using pairing, use the values of the IPC and more options to obtain the similarity measure, and selecting and displaying at least one result corresponding to the image containing the object for which the comparison indicates a degree of similarity between the query and the above-mentioned object.

According to the method according to the third object of the invention to measure the similarity can be based on M, where M=a*GP-S+CSS S, where GP-S is a measure of similarity between the additional parameters of the contours of the compared object, CSS-S - a measure of similarity between the IPC values for the contours of the objects being compared, and is a constant.

According to the method according to the third object of the present invention and may depend on the number and height of the peaks of the IPC.

As can be equal to 1, when the IPC.

Way of the search object in a still image or video image, by processing signals corresponding to images according to a fourth object of the invention contains the calculation of the measure of similarity between the contours of two objects using a view IPC-mentioned circuits and additional parameters reflecting the distribution shapes or masses in its original contour and a smoothed version of this circuit.

A brief description of the drawings Fig.1 is a block diagram of the system base video.

Fig.2 is a drawing of the outline of the object.

Fig.3 is a representation of the IPC circuit according to Fig.2.

The best implementation of the invention, the First implementation of Fig. 1 shows an automated system base video data according to this invention. This system includes a control unit 2 in the form of a computer, the display unit 4 in the form of a monitor, a pointing device 6 in the form of a mouse, the base 8 of the image data including the stored still images and video images, and a database 10 data descriptor, storing the descriptors of the objects or portions of objects appearing in the images stored in the database 8 of the image data.

The descriptor for each caller online who are in the 10 data descriptors. The control unit 2 receives the descriptors in the process under the control of appropriate software embodying the method described below.

First for loop of the given object to have a clear understanding of the IPC path. This is done by using a known method as described in one of the aforementioned articles.

More specifically, the circuit is expressed by the representation={(x(u) y(u), u[0, 1]}, where u is the parameter of the normalized arc length.

Contour smoothed by convolutionwith kernel g (u,) The Gaussian identifier. Zero crossing of the curvature of the unfolding curve check as. Zero crossing is identified using the following expressions for the curvature:,
where X(u,)=x(u)*g(u,); Y(u,)=y(u)*g(u,);
Xu(u,)=x(u)*gu(u,); Xuu(u,)=x(u)*guu(u,).

In the above expressions, * represents convolution, and subscripts represent derivatives.

The number parasocial aboveis convex curve without crossing zero.

Point (u,) of zero-crossings based on the graph, known as the image space of the IPC. This is reflected in many of the characteristics curves of the original circuit. Peaks characteristic curves are identified and the corresponding coordinates stand out and be remembered. In General, this gives a set of n coordinate pairs [(x1,y1), (x2,y2),..., (xn,yn)], where n is the number of peaks, xi is the position of the arc length of the i-th peak, yi is the height of this peak. These coordinates peaks represent the view of the IPC.

In addition to presenting the IPC, additional parameters are associated with this form to obtain a descriptor of the form. In this implementation of the additional parameters are the eccentricity and circularity "field prototype" for this form, where the scope of the prototype of this form represents the outline of this shape after the final step of smoothing, i.e. at the point equivalent to the value ofthe highest peak. For the scope of the prototype can be selected and other values of. The result is a descriptor of the form to form S in the form: {EPR, CPR, PEAK}, where EPR is the eccentricity of the field prototype, CPR - rounded is accordance with this invention.

Here, the base 10 data descriptors in the system of Fig.1 stores the descriptors form obtained according to the above method.

The user initiates the search by drawing the contour of the object on the display using a pointing device. The control unit 2 then obtains a handle to the form of the input circuit as described above. The control unit then performs interfacing comparison with each descriptor form, stored in this database.

Assume that the input circuit of the form S1 is compared with the memorized shape S2, and S1 and S2 are the corresponding descriptor:
S1: {EPR1, CPR1, REAK},
S2: {EPR2, CPR2, REAK},
where EPR means the eccentricity of the field prototype, CPR means the roundness of the field prototype, a PEAK mean the set of coordinates of the peaks in the image of the IPC (this set may be empty). The measure of similarity between two shapes is computed as follows.

M=a*(abs(EPR2-EPR1)/(EPR2+EPR1))+b*abs((CPR2-CPR1)/((CPR2+CPR1))+SM(PEAKS1, PEAKS2),
where a and b are two coefficients, S - a standard measure of similarity defined on two sets of peaks [1], a abs denotes the absolute value. SM is calculated by using a known algorithm mates which you can use the algorithms described in the aforementioned article the curveiimage and model curvemand their respective sets of peaks {(xi1,yi1), (xi2, yi2), . . ., (xin,yin)} and {(xm1,ym1) and (xm2, ym2),..., (xmn,ymn)} is computed measure of similarity. This measure of similarity is defined as the total price of a pair of peaks in the model with peaks in the image. The pair which minimizes the total price is determined using dynamic programming. The algorithm recursively matches the peaks from the model with the peaks of the image and calculates the price of each such pair. Each peak model can be paired with only one peak of the image, and each peak of the image can be paired with only one peak model. Some of the peaks of the model and the image may remain unpaired, and, for each unpaired peak is assigned a penalty price. Two peaks can be paired if their horizontal distance less than 0.2. The price of the pair represents the length of a straight line between two adjacent peaks. Price unpaired peak is its height.

More details on this algorithm works by creating and expanding a tree structure where the nodes correspond to the paired peaks:
1. To create the initial node, consisting of the most high and the falls in the 80% of the maximum of the maximum peaks of the image, create additional home site.

3. To initialize the initial price of each node created in 1 and 2, to the absolute difference of y-coordinates of the peaks of the model and the image associated with this node.

4. For each starting node 3 to compute the alpha shift IPC, defined as the difference (horizontal) coordinates x peaks model and image, paired in this initial node. The shift parameter will be different for each node.

5. For each starting node to create a list of peaks model and the peaks of the image. This list contains information which peaks still be mate. For each starting node to mark the peaks associated to this node as "conjugate", and all other peaks as "unpaired".

6. Recursively expand the node of the lower price (starting from each node created in steps 1-6 and accompany their child nodes) until then, until the conditions of paragraph 8. To expand a node use the following procedure:
7. The expansion of the node.

If there are unpaired at least one peak of the image and one peak model: select the maximum IPC curve image on the greatest scale, which does not involve (xip, yip). To make the add option is now selected peak has coordinates (xip-alpha, yip). To determine the position of the nearest peak of the curve model, which does not involve (xms, yms). If the horizontal distance between these two peaks is less than 0.2 (i.e., |xip-alpha-xms|<0,2), to produce the pairing of these two peaks and to determine the price of this pair as the length of a straight line between these two peaks. Add the price of this pair to the total price of this node. Delete the paired peaks from the appropriate lists, marking them as "connected". If the horizontal distance between these two peaks is greater than 0.2, this peak (xip,yip) image can not be paired. In this case, add its height yip to the total price and to delete only this peak (xip,yip) from the list of peaks in the image by marking it as "unpaired".

Otherwise, there are only the peaks of the image or there are only peaks model, the remaining unpaired):
To determine the price of a pair as the height of the highest unpaired peak image or model and remove this peak from the list.

8. If after expanding a node in p. 7 in both lists images and models no non-paired sites, the pairing is completed. The price of this node is a measure of similarity between the curve of the image and the model. Otherwise, go to p. 7 and expand the node N. the curve model. The final value of the pair is the smallest of the two.

The above steps are repeated for each model in the database.

Similarity measure appearing in the result of the comparison pair, are arranged in order, and the objects corresponding to the descriptors having a similarity measure that indicates the very close pair (i.e., here the lowest similarity measure), then appear on the display unit 4 to the user. The number of objects to be displayed, can be set in advance or selected by the user.

In an alternative embodiment to describe a form field prototype" can be used in a variety of settings. For example, you can use three Fourier coefficient for the curve. The measure of similarity may be determined as follows:
M=a*EUC(F1,F2)+SM(PEAKS1+PEAKS2),
where EUC is the Euclidean distance between the vectors F1 and F2, is generated from three main Fourier coefficients for the form image and the model, and is a constant, SM represents the degree of similarity to the peaks of the IPC, calculated using the method essentially described above.

Industrial applicability
The system according to this invention can, for example, be provided in the image library. Alternatively, the database may buy as a telephone line, or a network such as the Internet. Database of images and descriptors may include, for example, in a permanent storage device or data on a portable storage medium such as CD-ROM or DVD.

Components of the system as described can be implemented in software or hardware form. Although the invention is described in the form of a computer system, it may be embodied in other forms, for example using a specialized IP.

Concrete examples of ways of representing a two-dimensional shape of the object and the methods of calculation of values representing the similarity between the two forms, but can be any suitable such methods.

The invention can also be used, for example, for a pair of images of objects for the purposes of verification or for filtering.


Claims

1. The method of representation of an object appearing in an image by processing signals corresponding to the image according to which receive the scaled representation of the space of curvature (IPC) for the contour of the object by smoothing the contour of the object, receive at least one additional parameter reflecting rainy parameter as a descriptor of the form object.

2. The method according to p. 1, in which an additional parameter refers to the smoothed contour corresponding to the peak in the image in the IPC.

3. The method according to p. 2, in which an additional parameter refers to the smoothed contour corresponding to the highest peak in the image in the IPC.

4. The method according to any of paragraphs.1-3, in which an additional parameter corresponds to the eccentricity of the path.

5. The method according to any of paragraphs.1-4, in which an additional parameter corresponds to the circularity of the contour.

6. The method according to any of paragraphs.1-5, in which at least one additional parameter uses is based on the view pane.

7. The method according to p. 6, in which an additional parameter is the torque invariant region.

8. The method according to p. 6 or 7, in which an additional parameter based on Fourier descriptors.

9. The method according to p. 6, in which an additional parameter based on Zernike moments for the area covered by the path.

10. Way to represent the set of objects appearing in the image, by processing signals corresponding to images, according to which for each contour of the object determines whether the object contour convexity and concavity, and if the curvature in the circuit volume is 9, and if the curvature in the contour of the object there is no convexity and concavity, then get the handle of the form, including at least the additional parameter reflecting the shape of the contour of the object.

11. The method according to p. 10, in which an additional parameter for the object's path without convexity and concavity, based on moment invariants areas, the Fourier descriptors or the Zernike moments of the contour.

12. The way to find the object in the image by processing signals corresponding to images, according to which type the query in the form of a two-dimensional contour, get a handle to the above circuit using the method according to any of paragraphs.1-9, compare the mentioned query descriptor with each descriptor for a stored object using the procedure mapping using the values of the IPC and more options to obtain the similarity measure, and select and display at least one result corresponding to the image containing the object for which the comparison indicates a degree of similarity between the query and the above-mentioned object.

13. The method according to p. 12, in which the measure of similarity based on M, where M=aGP-S+CSS S, where GP-S is a measure of similarity between dopolnitelnye objects a is a constant.

14. The method according to p. 13, in which a depends on the number and height of the peaks of the IPC.

15. The method according to p. 13 or 14, in which a=1, when no peaks IPC associated with any circuit, and a=0 when at least one circuit has a peak IPC.

16. A computer system programmed to operate according to the method according to any one of paragraphs.1-15.

17. Machine-readable recording medium storing steps executable on a computer process for an embodiment of the method according to any one of paragraphs.1-15.

 

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