CN115100321A - Shape recognition and correction method and device based on hand-drawn track and storage medium - Google Patents
Shape recognition and correction method and device based on hand-drawn track and storage medium Download PDFInfo
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Abstract
The invention discloses a shape recognition and correction method, a device, equipment and a storage medium based on a hand-drawn track, wherein the method comprises the following steps: based on a pre-trained neural network model, performing large-scale classification recognition on the acquired hand-drawn track so as to enable the hand-drawn track to be distinguished into one of a closed graph and a non-closed graph; when the hand-drawn track is a closed graph, calculating inflection points existing in the hand-drawn track to determine the specific shape of the hand-drawn track; when the hand-drawn track is a non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn track to obtain the number of characteristic points, and determining the specific shape of the hand-drawn track according to the number of the characteristic points; and correcting the hand-drawn trajectory according to different specific shapes of the obtained hand-drawn trajectory and the inflection point or/and the characteristic point so as to fit the hand-drawn trajectory with the standard graph. The method and the device can improve the accuracy of identifying the hand-drawn geometric figure, and can quickly and accurately identify and correct the figure class drawn by the user.
Description
Technical Field
The invention relates to the technical field of pattern recognition, in particular to a shape recognition and correction method and device based on a hand-drawn track and a storage medium.
Background
Currently, many drawing tools directly use regular primitive input, such as Microsoft Office, Visio and most CAD systems, and require the user to select predefined standard graphics from a large number of menus and buttons during drawing, which also has the following disadvantages:
1) the input is inconvenient. When finding that a user draws a needed graph, the user usually clicks a mouse for multiple times to select, and particularly when a plurality of predefined graphs or objects exist, the user can hardly remember where to select the needed graph. For example, microsoft has a predefined set of graphics for the user to select from, and a complex interface makes it difficult for the user to feel comfortable.
2) The input is unnatural. Some applications, such as solution design, require a user to quickly record their design concept anytime and anywhere, rather than being tied to a particular detail, as opposed to traditional applications that target the final design. In these systems, the process of selecting the predefined standard object often interrupts the idea of the user, thereby preventing the user from smoothly embodying the design idea.
3) It is not suitable for small screen palm devices. For small screen palm devices that have only a pen input interface, this input is not practical. Since the large number of menus and buttons can strain an otherwise crowded screen, thereby squeezing the user's area of use.
With the continuous update of hardware devices, such as the appearance of handwriting boards, interactive hand-drawn sketch design based on the hardware devices is gradually becoming a new way for designers to design hand-drawn sketches. However, the degree of freedom of inputting the hand-drawn sketch is high, the input intention is related to various characteristics such as field background, thinking mode, hand-drawing habit and preference, the hand-drawing process is also influenced by various environmental factors such as graphic structure and equipment characteristics, and the structure and the internal relation of the hand-drawn graphic of the user have strong subjectivity. This makes hand-drawn recognition very difficult.
It can be seen that there is still much room for improvement in the recognition and correction of hand-drawn geometries.
Disclosure of Invention
In view of the above technical problems, the present invention provides a method, an apparatus, and a storage medium for shape recognition and correction based on a hand-drawn trajectory, so as to provide a scheme capable of quickly and accurately recognizing an input hand-drawn sketch.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to one aspect of the invention, a shape recognition and correction method based on a hand-drawn track is provided, which is characterized by comprising the following steps: based on a pre-trained neural network model, performing large-scale classification recognition on the acquired hand-drawn track so as to enable the hand-drawn track to be distinguished into one of a closed graph and a non-closed graph; when the hand-drawn track is the closed graph, calculating inflection points existing in the hand-drawn track to determine the specific shape of the hand-drawn track; when the hand-drawn track is the non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn track to obtain the number of characteristic points, and determining the specific shape of the hand-drawn track according to the number of the characteristic points; and correcting the hand-drawn trajectory according to different specific shapes of the obtained hand-drawn trajectory and the inflection point or/and the characteristic point so as to fit the hand-drawn trajectory with a standard graph.
Further, the closed figure at least comprises one of a circle, a polygon, a pentagram, a heart and a cloud, and the non-closed figure at least comprises one of a straight line, a parabola, a straight line with an arrow and a curve with an arrow.
Further, when the hand-drawn trajectory is one of a circle, a polygon, a pentagram, a heart and a cloud, calculating an inflection point existing in the hand-drawn trajectory to determine a specific shape of the hand-drawn trajectory specifically includes the following steps S201 to S204:
step S201: connecting a first straight line segment between the head point and the tail point of any selected line of the hand-drawn track, wherein the first straight line segment is a chord of the selected line;
step S202: obtaining a point on the selected line with the maximum distance from the first straight line segment, and calculating the distance between the point and the first straight line segment;
step S203: comparing the distance with a preset first threshold value, if the distance is smaller than the first threshold value, taking the first straight line segment as an approximate segment of the selected line, taking a connecting point of a plurality of approximate segments as the inflection point, and determining the specific shape of the hand-drawn trajectory according to the number of the inflection points;
step S204: if the distance is larger than the first threshold, selecting a point on the selected line with the largest distance from the first straight line segment as a splitting point, splitting the selected line into two segments, and executing steps S201-S203 on the two segments of the selected line respectively.
Further, when the hand-drawn trajectory is one of a straight line, a parabola, a straight line with an arrow, and a curve with an arrow, the calculating a curvature between every three adjacent data points of the hand-drawn trajectory to obtain a number of feature points, and determining a specific shape of the hand-drawn trajectory according to the number of feature points specifically includes:
setting the coordinates of each point on the hand-drawn track as (x) 1 ,y 1 ),(x 2 ,y 2 ),(x 3 ,y 3 ),...,(x n ,y n )；
By calculation of formula
The curvature is obtained as cur, wherein:
temp＝(a*a+b*b-c*c)/(2*a*b)；
a. b and c are three adjacent points, x 1-x 3 are x-axis coordinates of a, b and c respectively, and y 1-y 3 are y-axis coordinates of a, b and c respectively;
calculating the difference in curvature: dcur [ n ] ═ cur [ n +1] -cur [ n ];
since dcur [ n ]. multidur [ n +1] <0and cur [ n ] > threshold;
n is the position of the characteristic point, and threshold is an adjustable second threshold;
and obtaining the specific shape of the hand-drawn track according to the number of the characteristic points.
Further, the correcting the hand-drawn trajectory to fit the hand-drawn trajectory to a standard graph specifically includes: when the specific shape of the hand-drawn track is a straight line, connecting the head and the tail of the hand-drawn track to generate a new straight line; when the specific shape of the hand-drawn track is a parabola, connecting head and tail points of the hand-drawn track into a second straight-line segment, setting a point, which is farthest away from the second straight-line segment, in the hand-drawn track as a vertex of the parabola, splitting the hand-drawn track into two segments from the vertex, and smoothly connecting the two segments of the hand-drawn track by using a cubic Bezier curve respectively to generate a new parabola; when the specific trajectory of the hand-drawn trajectory is a circle, selecting a central point of the hand-drawn trajectory as a circle center, calculating to obtain an average distance between each point of the hand-drawn trajectory and the central point, and generating a new circle by taking the average distance as a radius; when the specific shape of the hand-drawn track is an ellipse, calculating a long axis and a short axis according to the auxiliary circumscribed rectangle of the hand-drawn track, and generating a new ellipse according to an ellipse formula; when the specific shape of the hand-drawn track is a polygon, calculating an included angle between connecting lines connected with the same inflection point, determining that the hand-drawn track is one of a triangle, a quadrangle, a pentagon and a pentagram according to the angle of the included angle and the number of the inflection points, and generating a new shape to replace the original hand-drawn track; and when the specific shape of the hand-drawn track is heart-shaped or cloud-shaped, drawing a heart-shaped or cloud-shaped symmetrically arranged and bordering each side of the auxiliary circumscribed rectangle in the auxiliary circumscribed rectangle of the hand-drawn track.
Further, when the specific shape of the hand-drawn trajectory is a straight line or a parabola and is provided with an arrow, the length of a line segment between a plurality of feature points is calculated, the line segment between two feature points with the longest length is used as a trunk part of the hand-drawn trajectory, the trunk part is corrected, and the rest part of the hand-drawn trajectory is replaced by a preset arrow shape.
Further, when the number of the inflection points is three, connecting the three inflection points to form an initial triangle, and calculating the included angle of the initial triangle, wherein: if the three included angles are equal to 60 degrees within a first error range, correcting the initial triangle into an equilateral triangle, and calculating the position of a third point of the equilateral triangle according to the positions of two inflection points; if two included angles are equal within a second set error range and the difference between the included angles and the degree of the rest included angle exceeds a third threshold value, correcting the initial triangle into an isosceles triangle, taking the two included angles equal within the error of 10 degrees as two base angles, and calculating the vertex coordinates of the isosceles triangle; if one included angle is equal to 90 degrees within a third error range, correcting the initial triangle into a right-angled triangle;
when the number of the inflection points is four, combining the four inflection points in pairs to form an initial quadrangle in sequence, and calculating the included angle of the initial quadrangle, wherein: if three included angles are equal to 90 degrees within a fourth error range, correcting the initial quadrangle into a rectangle, and calculating the coordinates of the remaining two points according to the position of one edge and the length of the adjacent edge; if the opposite angles of the initial quadrangle are equal in a fifth error range, correcting the initial quadrangle into a parallelogram; if the opposite angles of the initial quadrangle are equal in the fifth error range and the lengths of the four sides are equal in the sixth error range, correcting the initial quadrangle into a rhombus;
when the number of the inflection points is five, sequentially connecting the five inflection points into an initial pentagon, and calculating the included angle of the initial pentagon, wherein: and if four included angles are smaller than 90 degrees, correcting the initial pentagon into a pentagon.
Further, correct for the pentagon initial pentagon to the pentagon, specifically include: setting the center of the hand-drawn track as a circle center, drawing a circle by taking the average distance from five inflection points to the circle center as a radius, and dividing the circle into five equal parts by taking the intersection point of a connecting line of one inflection point and the circle center on the circle as a starting point to obtain five vertexes of the five-pointed star.
According to a second aspect of the present disclosure, there is provided a shape recognition and correction apparatus based on a hand-drawn trajectory, including: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to: performing large-scale classification recognition on the obtained hand-drawn track based on a pre-trained neural network model so as to enable the hand-drawn track to be distinguished into one of a closed graph and a non-closed graph; when the hand-drawn trajectory is the closed graph, calculating an inflection point existing in the hand-drawn trajectory to determine the specific shape of the hand-drawn trajectory; when the hand-drawn track is the non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn track to obtain the number of characteristic points, and determining the specific shape of the hand-drawn track according to the number of the characteristic points; and correcting the hand-drawn trajectory according to the obtained difference of the specific shape of the hand-drawn trajectory and the inflection point or/and the characteristic point so as to fit the hand-drawn trajectory with a standard graph.
According to a third aspect of the present disclosure, there is provided a computer-readable storage medium storing a computer program, which when executed by a processor, performs the above-mentioned shape recognition and correction method based on a hand-drawn trajectory.
The technical scheme of the disclosure has the following beneficial effects:
according to the shape recognition and correction method, device, equipment and storage medium based on the hand-drawn track, the accuracy of recognition of the hand-drawn geometric figure can be improved, and the figure type drawn by a user can be recognized and corrected quickly and accurately. The touch screen is high in applicability, and is suitable for drawing tools such as a traditional hand drawing board and the like and also suitable for the existing mobile touch equipment.
Drawings
Fig. 1 is a flowchart of a shape recognition and correction method based on a hand-drawn trajectory in an embodiment of the present specification;
FIG. 2 is a flowchart of a method for calculating an inflection point of a freehand trajectory in an embodiment of the present disclosure;
FIG. 3 is a schematic view of the correction of straight lines in an embodiment of the present disclosure;
FIG. 4 is a schematic view of the correction of a parabola in an embodiment of the present disclosure;
FIG. 5 is a schematic view of correction of a heart shape in an embodiment of the present disclosure;
FIG. 6 is a schematic view of correcting a cloud shape in an embodiment of the present disclosure;
FIG. 7 is a schematic view of a parabolic arrowed correction in an embodiment of the present disclosure;
FIG. 8 is a graph illustrating the correction result of parabolic arrowed lines in an embodiment of the present disclosure;
FIG. 9 is a schematic diagram of a shape recognition and correction device based on a hand-drawn trajectory according to an embodiment of the present disclosure;
fig. 10 is a terminal device for implementing a shape recognition and correction method based on a hand-drawn trajectory in an embodiment of the present specification;
fig. 11 is a computer-readable storage medium for implementing a shape recognition and correction method based on a hand-drawn trajectory in an embodiment of the present specification.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Furthermore, the drawings are only schematic illustrations of the present disclosure. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
As shown in fig. 1, an embodiment of the present disclosure provides a shape recognition and correction method based on a hand-drawn trajectory, where an execution subject of the method may be a terminal device, where the terminal device may be a mobile phone, a tablet computer, a personal computer, and the like. The method may specifically include the following steps S101 to S103:
in step S101, based on a pre-trained neural network model, a large-scale classification recognition is performed on the acquired hand-drawn trajectory, so that the hand-drawn trajectory is distinguished as one of a closed graph and a non-closed graph.
The pre-trained neural network model, namely the recognition model trained by adopting a plurality of geometric samples, can perform basic recognition on the hand-drawn track. The hand-drawn trajectory may be drawing information generated from a drawing device such as a hand-drawn board, touch screen, or the like. The closed figure means that lines of the hand-drawn track are closed, such as circles, polygons and the like. The non-closed graph refers to non-closed lines of the hand-drawn track, such as straight lines, curved lines and the like.
In step S102, when the hand-drawn trajectory is the closed graph, calculating an inflection point existing in the hand-drawn trajectory to determine a specific shape of the hand-drawn trajectory; when the hand-drawn trajectory is the non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn trajectory to obtain the number of characteristic points, and determining the specific shape of the hand-drawn trajectory according to the number of the characteristic points.
The neural network model identifies the basic category of the hand-drawn track, such as a circle, a polygon, a pentagram, a heart, a cloud and the like in a closed figure, or a straight line, a parabola, a straight line with an arrow, a curve with an arrow and the like in a non-closed figure, and then needs to obtain the specific shape of the hand-drawn track through calculation, such as a triangle, a quadrangle, a pentagon and the like in a polygon, and then identifies the triangle as an isosceles triangle, an equilateral triangle, a right triangle, a common triangle, and a quadrangle as a rectangle, a rhombus, a parallelogram and the like in the specific shape. The identification of a specific shape can be obtained by calculating the number of inflection points or curvature values.
In step S103, the hand-drawn trajectory is corrected according to the obtained difference in the specific shape of the hand-drawn trajectory and the inflection point or/and the feature point, so that the hand-drawn trajectory fits a standard graph.
After the specific shape of the hand-rail track is obtained, the definition of the hand-drawn track is only realized, and the hand-drawn track needs to be corrected when applied to drawing, so that the obtained graph is more exquisite and neat.
In one embodiment, as shown in fig. 2, when the hand-drawn trajectory is one of a circle, a polygon, a pentagram, a heart, and a cloud, the step S102 specifically performs the following steps S201 to S204:
step S201: and a first straight line segment AB is connected between the head point A, B and the tail point A, B of any selected line of the hand-drawn locus, and the first straight line segment AB is a chord of the selected line.
The line segment of the whole hand-drawn track is a curve due to the characteristic of hand drawing, so the selected line is generally a curve with a certain radian.
Step S202: and obtaining a point C with the maximum distance from the first straight line segment AB on the selected line, and calculating the distance d between the point C and the first straight line segment AB.
Step S203: and comparing the distance d with a preset first threshold, if the distance d is smaller than the first threshold, taking the first straight line segment AB as an approximate segment of the selected line, calculating to obtain a plurality of approximate segments, taking a connecting point of the approximate segments as the inflection point, and determining the specific shape of the hand-drawn trajectory according to the number of the inflection points.
Step S204: if the distance is greater than the first threshold, selecting a point C on the selected line with the maximum distance from the first straight line segment as a splitting point, splitting the selected line into two segments of AC and BC, and continuously executing the steps S201 to S203 for the two segments of AC and BC respectively.
In one embodiment, when the hand-drawn trajectory is one of a straight line, a parabola, a straight line with an arrow, and a curved line with an arrow, the step S102 specifically includes the following calculation method:
setting the coordinates of each point on the hand-drawn track as (x) 1 ,y 1 ),(x 2 ,y 2 ),(x 3 ,y 3 ),...,(x n ,y n )；
By calculation of formula
The curvature is obtained as cur, wherein:
temp＝(a*a+b*b-c*c)/(2*a*b)；
a. b and c are three adjacent points, x 1-x 3 are x-axis coordinates of a, b and c respectively, and y 1-y 3 are y-axis coordinates of a, b and c respectively;
calculating the difference in curvature: dcur [ n ] ═ cur [ n +1] -cur [ n ];
since dcur [ n ]. multidur [ n +1] <0and cur [ n ] > threshold;
n is the position of the characteristic point, the threshold is an adjustable second threshold, the threshold can be adjusted according to specific needs, and the smaller the value is, the more characteristic points are found.
And obtaining the specific shape of the hand-drawn track according to the number of the characteristic points.
In an embodiment, after obtaining the specific shape indicated in the above example, the hand-drawn trajectory needs to be corrected according to the type of the specific shape, so that the hand-drawn trajectory fits the standard graph, and the specific correction method includes:
as shown in fig. 3, when the specific shape of the hand-drawn trajectory is a straight line, two points from the head to the tail of the hand-drawn trajectory are connected to generate a new straight line. Wherein, the dotted line is a hand-drawn track, and the solid line is a corrected straight line.
As shown in fig. 4, when the specific shape of the hand-drawn trajectory is a parabola, connecting the head and the tail of the hand-drawn trajectory into a second straight line segment, setting a point in the hand-drawn trajectory, which is farthest from the second straight line segment, as a vertex of the parabola, splitting the hand-drawn trajectory into two segments from the vertex, and smoothly connecting the two segments of the hand-drawn trajectory with cubic bezier curves respectively to generate a new parabola.
When the specific trajectory of the hand-drawn trajectory is a circle, selecting a central point of the hand-drawn trajectory as a circle center, calculating to obtain an average distance between each point of the hand-drawn trajectory and the central point, and generating a new circle by taking the average distance as a radius;
when the specific shape of the hand-drawn track is an ellipse, calculating a long axis and a short axis according to the auxiliary circumscribed rectangle of the hand-drawn track, and generating a new ellipse according to an ellipse formula;
when the specific shape of the hand-drawn track is a polygon, calculating an included angle between connecting lines connected with the same inflection point, determining that the hand-drawn track is one of a triangle, a quadrangle, a pentagon and a pentagon according to the angle of the included angle and the number of the inflection points, and generating a new shape to replace the original hand-drawn track;
and when the specific shape of the hand-drawn track is heart-shaped or cloud-shaped, drawing a heart-shaped or cloud-shaped symmetrically arranged and bordered by each side of the auxiliary circumscribed rectangle in the auxiliary circumscribed rectangle of the hand-drawn track.
As a supplement, when the specific shape of the hand-drawn trajectory is a heart shape, as shown in fig. 5, the auxiliary circumscribed rectangle of the heart shape has a length H and a width W, the upper half of the heart shape is connected by two semicircles, and the radius r is W/4. Taking the center point of the graph as a center point, the point closest to the center point in all the points drawn is considered as the concave point of the heart shape, namely the midpoint of O1 and O2. And respectively searching one tenth of total points of the graph towards two sides by taking the concave points as starting points, and respectively connecting the concave points to calculate vector bisectors of the two lines, wherein the angle of the bisector is the orientation position of the heart shape. The lower half is connected by calculation using the formula u (x) -3 r (sqrt (1-sqrt ((abs (x))/(2 r)))).
When the specific shape of the hand-drawn trajectory is a cloud shape, as shown in fig. 6, the center point of the hand-drawn trajectory graph is taken as the center of a circle, and the length and width of the minimum auxiliary circumscribed rectangle are taken as the length and width of the cloud. The left side and the right side are respectively provided with four circular arcs,
centre angle120 degrees;
the central angle is 180 degrees;
a central angle of 120 degrees;
the central angle is 90 degrees. The upper side and the lower side are respectively connected by n arcs with central angles of 90 degrees, and Rn is R4. Therefore, the original hand-drawn track can be corrected without destroying the drawing habit and rule of the original hand-drawn track.
In one embodiment, when the number of the inflection points is three, connecting the three inflection points to an initial triangle, and calculating the included angle of the initial triangle, wherein:
if the three included angles are equal to 60 degrees within a first error range, correcting the initial triangle into an equilateral triangle, and calculating the position of a third point of the equilateral triangle according to the positions of two inflection points;
if two included angles are equal within a second set error range and the difference between the two included angles and the degree of the remaining included angle exceeds a third threshold value, correcting the initial triangle into an isosceles triangle, taking the two included angles equal within an error of 10 degrees as two base angles, and calculating the vertex coordinates of the isosceles triangle;
if one included angle is equal to 90 degrees within a third error range, correcting the initial triangle into a right-angled triangle;
when the number of the inflection points is four, combining the four inflection points in pairs to form an initial quadrangle in sequence, and calculating the included angle of the initial quadrangle, wherein:
if three included angles are equal to 90 degrees within a fourth error range, correcting the initial quadrangle into a rectangle, and calculating the coordinates of the remaining two points according to the position of one edge and the length of the adjacent edge;
if the opposite angles of the initial quadrangle are equal in a fifth error range, correcting the initial quadrangle into a parallelogram;
if the opposite angles of the initial quadrangle are equal in the fifth error range and the lengths of the four sides are equal in the sixth error range, the initial quadrangle is corrected into a rhombus;
when the number of the inflection points is five, sequentially connecting the five inflection points into an initial pentagon, and calculating the included angle of the initial pentagon, wherein:
and if four included angles are smaller than 90 degrees, correcting the initial pentagon into a pentagon.
As a supplement, the correcting the initial pentagon into a pentagon specifically includes:
setting the center of the hand-drawn track as a circle center, drawing a circle by taking the average distance from five inflection points to the circle center as a radius, and dividing the circle into five equal parts by taking the intersection point of a connecting line of one inflection point and the circle center on the circle as a starting point to obtain five vertexes of the five-pointed star. And the correction of the common pentagon is only needed to be connected with five points in sequence. In addition, the five-pointed star also needs to calculate coordinates of five points of the indent and then sequentially connect ten points, which can be calculated by the characteristics of the five-pointed star.
In an embodiment, when the specific shape of the hand-drawn trajectory is a straight line or a parabola and is provided with an arrow, the length of a line segment between a plurality of feature points is calculated, a line segment between two feature points with the longest length is used as a trunk part of the hand-drawn trajectory, the trunk part is corrected, and the remaining part of the hand-drawn trajectory is replaced by a preset arrow shape.
Because the arrow head section has a plurality of sections of irregular broken lines, the trunk position of the hand-drawn track graph and the position drawn by the arrow head need to be calculated for the corrected fit degree. At this time, parameters such as the length of each irregular line segment need to be calculated to search the trunk and the arrow. The principle of straight line with arrow head correction is the same as that of straight line correction, and the principle of curve with arrow head partial correction is the same as that of parabola correction.
As shown in fig. 7, the characteristic points P1, P2, P3 are found according to the curvature method, and the length of each curve is calculated:
d1 ═ Begin, P1|, d2 ═ P1, P2|, d3 ═ P2, P3|, d4 ═ P3, End |, the longest segment is the part of the curve, the rest is replaced by the arrow part, and the correction result is shown in fig. 8.
Based on the same idea, an exemplary embodiment of the present disclosure also provides a shape recognition and correction device based on a hand-drawn trajectory, as shown in fig. 9, the shape recognition and correction device 900 based on a hand-drawn trajectory includes: the identification module 1001 is used for performing large-scale classification identification on the acquired hand-drawn track based on a pre-trained neural network model so as to enable the hand-drawn track to be distinguished into one of a closed graph and a non-closed graph; a calculating module 1002, configured to calculate an inflection point existing in the hand-drawn trajectory when the hand-drawn trajectory is the closed graph, so as to determine a specific shape of the hand-drawn trajectory; when the hand-drawn track is the non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn track to obtain the number of characteristic points, and determining the specific shape of the hand-drawn track according to the number of the characteristic points; the correcting module 1003 corrects the hand-drawn trajectory according to the obtained difference of the specific shape of the hand-drawn trajectory and the inflection point or/and the feature point, so that the hand-drawn trajectory fits a standard graph.
By adopting the shape recognition and correction device based on the hand-drawn track, the accuracy of recognition of the hand-drawn geometric figure can be improved, and the figure type drawn by a user can be recognized quickly and accurately and corrected.
The specific details of each module/unit in the above-mentioned apparatus have been described in detail in the method section, and the details that are not disclosed may refer to the contents of the method section, and thus are not described again.
Based on the same idea, the embodiment of the present specification further provides a shape recognition and correction device based on a hand-drawn trajectory, as shown in fig. 10.
The shape recognition and correction device based on the hand-drawn trajectory may be the terminal device or the server provided in the above embodiments.
The shape recognition and correction device based on the hand-drawn trajectory may have a relatively large difference due to different configurations or performances, and may include one or more processors 1001 and a memory 1002, and one or more stored applications or data may be stored in the memory 1002. Memory 1002 may include readable media in the form of volatile memory units, such as random access memory units (RAM) and/or cache memory units, among others, and may further include read-only memory units. The application programs stored in memory 1002 may include one or more program modules (not shown), including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment. Still further, the processor 1001 may be configured to communicate with the memory 1002 to execute a series of computer-executable instructions in the memory 1002 on the hand-drawn trajectory based shape recognition and correction device. The hand-drawn trace-based shape recognition and correction device may also include one or more power sources 1003, one or more wired or wireless network interfaces 1004, one or more I/O interfaces (input output interfaces) 1005, one or more external devices 1006 (e.g., keyboard, hand-drawn tablet, bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with the device, and/or any devices (e.g., router, modem, etc.) that enable the device to communicate with one or more other computing devices. Such communication may occur through I/O interface 1005. Also, the device may communicate with one or more networks (e.g., a Local Area Network (LAN)) via a wired or wireless interface 1004.
In particular, in the present embodiment, the shape recognition and correction device based on a hand-drawn trajectory comprises a memory, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may comprise one or more modules, and each module may comprise a series of computer-executable instructions for the shape recognition and correction device based on a hand-drawn trajectory, and the one or more programs configured to be executed by the one or more processors comprise computer-executable instructions for:
based on a pre-trained neural network model, performing large-scale classification recognition on the acquired hand-drawn track so as to enable the hand-drawn track to be distinguished into one of a closed graph and a non-closed graph; when the hand-drawn trajectory is the closed graph, calculating an inflection point existing in the hand-drawn trajectory to determine the specific shape of the hand-drawn trajectory; when the hand-drawn track is the non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn track to obtain the number of characteristic points, and determining the specific shape of the hand-drawn track according to the number of the characteristic points; and correcting the hand-drawn trajectory according to different specific shapes of the obtained hand-drawn trajectory and the inflection point or/and the characteristic point so as to fit the hand-drawn trajectory with a standard graph.
Based on the same idea, the exemplary embodiments of the present disclosure also provide a computer-readable storage medium on which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure described in the above-mentioned "exemplary methods" section of this specification, when the program product is run on the terminal device.
Referring to fig. 11, a program product 1100 for implementing the above method according to an exemplary embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the exemplary embodiments of the present disclosure.
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit, according to exemplary embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A shape recognition and correction method based on a hand-drawn track is characterized by comprising the following steps:
based on a pre-trained neural network model, performing large-scale classification recognition on the acquired hand-drawn track so as to enable the hand-drawn track to be distinguished into one of a closed graph and a non-closed graph;
when the hand-drawn track is the closed graph, calculating inflection points existing in the hand-drawn track to determine the specific shape of the hand-drawn track; when the hand-drawn track is the non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn track to obtain the number of characteristic points, and determining the specific shape of the hand-drawn track according to the number of the characteristic points;
and correcting the hand-drawn trajectory according to different specific shapes of the obtained hand-drawn trajectory and the inflection point or/and the characteristic point so as to fit the hand-drawn trajectory with a standard graph.
2. The method for shape recognition and correction based on hand-drawn trajectory according to claim 1, wherein the closed figure comprises at least one of a circle, a polygon, a pentagram, a heart and a cloud, and the non-closed figure comprises at least one of a straight line, a parabola, a straight line with an arrow and a curved line with an arrow.
3. The method for shape recognition and correction based on a hand-drawn trajectory according to claim 2, wherein when the hand-drawn trajectory is one of a circle, a polygon, a pentagram, a heart and a cloud, the calculating of the inflection point existing in the hand-drawn trajectory to determine the specific shape of the hand-drawn trajectory specifically includes the following steps S301 to S304:
step S201: connecting a first straight line segment between the head point and the tail point of any selected line of the hand-drawn track, wherein the first straight line segment is a chord of the selected line;
step S202: obtaining a point on the selected line with the maximum distance from the first straight line segment, and calculating the distance between the point and the first straight line segment;
step S203: comparing the distance with a preset first threshold value, if the distance is smaller than the first threshold value, taking the first straight line segment as an approximate segment of the selected line, taking a connecting point of a plurality of approximate segments as the inflection point, and determining the specific shape of the hand-drawn trajectory according to the number of the inflection points;
step S204: if the distance is larger than the first threshold, selecting a point on the selected line with the largest distance from the first straight line segment as a splitting point, splitting the selected line into two segments, and executing steps S201-S203 on the two segments of the selected line respectively.
4. The method for shape recognition and correction based on the hand-drawn trajectory according to claim 2, wherein when the hand-drawn trajectory is one of a straight line, a parabola, a straight line with an arrow, and a curved line with an arrow, the calculating a curvature between every three adjacent data points of the hand-drawn trajectory to obtain a number of feature points, and determining a specific shape of the hand-drawn trajectory according to the number of feature points specifically comprises:
setting the coordinate of each point on the hand-drawn track as (x) 1 ,y 1 ),(x 2 ,y 2 ),(x 3 ,y 3 ),...,(x n ,y n )；
By calculation of formula
The curvature is obtained as cur, wherein:
temp＝(a*a+b*b-c*c)/(2*a*b)；
a. b and c are three adjacent points, x 1-x 3 are x-axis coordinates of a, b and c respectively, and y 1-y 3 are y-axis coordinates of a, b and c respectively;
calculating the difference in curvature: dcur [ n ] ═ cur [ n +1] -cur [ n ];
since dcur [ n ]. multidur [ n +1] <0and cur [ n ] > threshold;
n is the position of the characteristic point, and threshold is an adjustable second threshold;
and obtaining the specific shape of the hand-drawn track according to the number of the characteristic points.
5. The method for shape recognition and correction based on the hand-drawn trajectory according to claim 1, wherein the correcting the hand-drawn trajectory so as to fit the hand-drawn trajectory to a standard graph specifically comprises:
when the specific shape of the hand-drawn track is a straight line, connecting the head and the tail of the hand-drawn track to generate a new straight line;
when the specific shape of the hand-drawn track is a parabola, connecting head and tail points of the hand-drawn track into a second straight-line segment, setting a point, which is farthest away from the second straight-line segment, in the hand-drawn track as a vertex of the parabola, splitting the hand-drawn track into two segments from the vertex, and smoothly connecting the two segments of the hand-drawn track by using a cubic Bezier curve respectively to generate a new parabola;
when the specific track of the hand-drawn track is a circle, selecting a central point of the hand-drawn track as a circle center, calculating to obtain an average distance between each point of the hand-drawn track and the central point, and generating a new circle by taking the average distance as a radius;
when the specific shape of the hand-drawn track is an ellipse, calculating a long axis and a short axis according to the auxiliary circumscribed rectangle of the hand-drawn track, and generating a new ellipse according to an ellipse formula;
when the specific shape of the hand-drawn track is a polygon, calculating an included angle between connecting lines connected with the same inflection point, determining that the hand-drawn track is one of a triangle, a quadrangle, a pentagon and a pentagram according to the angle of the included angle and the number of the inflection points, and generating a new shape to replace the original hand-drawn track;
and when the specific shape of the hand-drawn track is heart-shaped or cloud-shaped, drawing a heart-shaped or cloud-shaped symmetrically arranged and bordered by each side of the auxiliary circumscribed rectangle in the auxiliary circumscribed rectangle of the hand-drawn track.
6. The method for shape recognition and correction based on the hand-drawn trajectory according to claim 5, wherein when the specific shape of the hand-drawn trajectory is a straight line or a parabolic line and is provided with an arrow, the length of a line segment between a plurality of feature points is calculated, the line segment between two feature points with the longest length is used as a trunk portion of the hand-drawn trajectory, the trunk portion is corrected, and the remaining portion of the hand-drawn trajectory is replaced with a preset arrow shape.
7. The shape recognition and correction method based on the hand-drawn trajectory according to claim 5, wherein when the number of the inflection points is three, the three inflection points are connected to form an initial triangle, and the included angle of the initial triangle is calculated, wherein:
if the three included angles are equal to 60 degrees within a first error range, correcting the initial triangle into an equilateral triangle, and calculating the position of a third point of the equilateral triangle according to the positions of two inflection points;
if two included angles are equal within a second set error range and the difference between the two included angles and the degree of the remaining included angle exceeds a third threshold value, correcting the initial triangle into an isosceles triangle, taking the two included angles equal within an error of 10 degrees as two base angles, and calculating the vertex coordinates of the isosceles triangle;
if one included angle is equal to 90 degrees within a third error range, correcting the initial triangle into a right-angled triangle;
when the number of the inflection points is four, combining the four inflection points in pairs to form an initial quadrangle in sequence, and calculating the included angle of the initial quadrangle, wherein:
if three included angles are equal to 90 degrees within a fourth error range, correcting the initial quadrangle into a rectangle, and calculating the coordinates of the remaining two points according to the position of one edge and the length of the adjacent edge;
if the opposite angles of the initial quadrangle are equal in a fifth error range, correcting the initial quadrangle into a parallelogram;
if the opposite angles of the initial quadrangle are equal in the fifth error range and the lengths of the four sides are equal in the sixth error range, correcting the initial quadrangle into a rhombus;
when the number of the inflection points is five, sequentially connecting the five inflection points into an initial pentagon, and calculating the included angle of the initial pentagon, wherein:
and if four included angles are smaller than 90 degrees, correcting the initial pentagon into a pentagon.
8. The shape recognition and correction method based on the hand-drawn trajectory according to claim 7, wherein the correcting the initial pentagon into a pentagon specifically comprises:
setting the center of the hand-drawn track as a circle center, drawing a circle by taking the average distance from five inflection points to the circle center as a radius, and dividing the circle into five equal parts by taking the intersection point of a connecting line of one inflection point and the circle center on the circle as a starting point to obtain five vertexes of the five-pointed star.
9. A shape recognition and correction device based on hand-drawn trajectories, comprising:
a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to: based on a pre-trained neural network model, performing large-scale classification recognition on the acquired hand-drawn track so as to enable the hand-drawn track to be distinguished into one of a closed graph and a non-closed graph;
when the hand-drawn trajectory is the closed graph, calculating an inflection point existing in the hand-drawn trajectory to determine the specific shape of the hand-drawn trajectory; when the hand-drawn track is the non-closed graph, calculating the curvature between every three adjacent data points of the hand-drawn track to obtain the number of characteristic points, and determining the specific shape of the hand-drawn track according to the number of the characteristic points;
and correcting the hand-drawn trajectory according to the obtained difference of the specific shape of the hand-drawn trajectory and the inflection point or/and the characteristic point so as to fit the hand-drawn trajectory with a standard graph.
10. A computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the method for shape recognition and correction based on a hand-drawn trajectory according to any one of claims 1 to 8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116309942A (en) * | 2023-05-11 | 2023-06-23 | 北京元跃科技有限公司 | Method and system for correcting graphic shape of mobile equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116309942A (en) * | 2023-05-11 | 2023-06-23 | 北京元跃科技有限公司 | Method and system for correcting graphic shape of mobile equipment |
| CN116309942B (en) * | 2023-05-11 | 2024-01-19 | 北京元跃科技有限公司 | Method and system for correcting graphic shape of mobile equipment |
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