WO2015188480A1

WO2015188480A1 - Digital image processing method, intelligent early education server, and intelligent early education client

Info

Publication number: WO2015188480A1
Application number: PCT/CN2014/086326
Authority: WO
Inventors: 封娟; 孙放宽
Original assignee: 中兴通讯股份有限公司
Priority date: 2014-06-11
Filing date: 2014-09-11
Publication date: 2015-12-17
Also published as: CN105205059A

Abstract

A digital image processing method applied to an intelligent early education server. The digital image processing method comprises: receiving picture data sent by a client; extracting characteristic information of the picture data and matching the characteristic information with tree species characteristics in a pre-established vocabulary tree; when the matching is successful, acquiring a pre-bound multimedia file corresponding to the tree species characteristics; and sending the multimedia file to the client for playing by the client. Also provided are another digital image processing method, an intelligent early education server, and an intelligent early education client. The solution can increase the interactivity and interest of early education.

Description

Digital image processing method, intelligent early education server and intelligent early education client

Technical field

The present invention relates to the field of digital signal processing technologies, and in particular, to a digital image processing method, an intelligent early education server, and an intelligent early education client.

Background technique

Early education machine is an electronic product between traditional toys and educational products that promotes children's interest in early childhood education. The early education function can comprehensively train children's learning ability. It combines multiple intelligence education theories, selects the theme scene according to children's life experience and psychological characteristics, and combines English, Pinyin literacy, mathematical logic, potential development, natural common sense, parent-child interaction, entertainment and morality. The contents of the eight fields are integrated into various themes, and the knowledge in the early education machine is comprehensive and clearly classified.

However, most of the current early education machines are similar to a story machine, and they can only be used as a cartoon-type recording player, which lacks interactivity and fun.

The above content is only used to assist in understanding the technical solutions of the present invention, and does not constitute an admission that the above is prior art.

Summary of the invention

The main purpose of the present invention is to increase the interactivity and interest of early education.

To achieve the above objective, an embodiment of the present invention provides a digital image processing method, which is applied to an intelligent early education server, and includes:

Receiving picture data sent by the client;

Extracting feature information of the picture data, and matching the feature information with a tree species feature in a pre-established vocabulary tree;

When the matching is successful, acquiring a pre-bound multimedia file corresponding to the tree species feature;

The multimedia file is sent to the client for the client to play.

Preferably, before the step of receiving the picture data sent by the client, the digital image processing method further includes:

Collect sample image data;

Binding each sample image data to a multimedia file;

Extracting tree species features of the sample picture data, training the sample picture data according to the tree species characteristics, and establishing a vocabulary tree.

Preferably, the step of extracting feature information of the picture data comprises:

Feature information of the point of interest of the picture data is extracted, and the feature information of the point of interest includes a color feature and an edge feature of the point of interest.

To achieve the above objective, the embodiment of the present invention further provides a digital image processing method, which is applied to a smart early education client, and includes:

Obtaining image data, and transmitting the image data to a smart early education server;

Receiving a multimedia file obtained by the smart early education server according to the picture data;

Play the multimedia file.

Preferably, before the step of playing the multimedia file, the digital image processing method further includes:

Determining whether the type of the multimedia file is a 3D type;

If the multimedia file is a 3D type, the step of performing 3D rendering on the multimedia file is performed first, and then the step of playing the multimedia file is performed.

To achieve the above objective, an embodiment of the present invention further provides an intelligent early education server, including:

a receiving module, configured to receive image data sent by the client;

a matching module, configured to extract feature information of the picture data, and match the feature information with a tree species feature in a pre-established vocabulary tree;

Obtaining a module, configured to acquire a pre-bound multimedia file corresponding to the tree species feature when the matching is successful;

The sending module is configured to send the multimedia file to the client for the client to play.

Preferably, the intelligent early education server further includes:

The acquisition module is configured to collect sample picture data;

a binding module configured to bind each sample picture data to a multimedia file;

And establishing a module, configured to extract a tree species feature of the sample picture data, train the sample picture data according to the tree species feature, and establish a vocabulary tree.

Preferably, the matching module is configured to extract feature information of a point of interest of the picture data, and the feature information of the point of interest includes a color feature and an edge feature of the point of interest.

To achieve the above objective, the embodiment of the present invention further provides an intelligent early education client, including:

Obtaining a module, configured to acquire image data, and send the image data to a smart early education server;

a receiving module, configured to receive a multimedia file acquired by the smart early education server according to the picture data;

a play module, configured to play the multimedia file.

Preferably, the smart early education client further includes:

a determining module, configured to determine whether the type of the multimedia file is a 3D type;

And a rendering module, configured to perform 3D rendering on the multimedia file if the multimedia file is a 3D type.

The digital image processing method, the intelligent early education server and the intelligent early education client provided by the embodiment of the present invention acquire the feature data of the picture data and the pre-established by acquiring the picture data in the story book or the textbook on the client and sending the image data to the server. The tree species features in the vocabulary tree are matched. When the matching is successful, the pre-bound multimedia file corresponding to the tree species feature is sent to the client, and the invention can combine the early education machine with the digital image processing technology and the camera of the early education machine. When you go to the picture, you can play the multimedia files related to the picture, and display the pictures in the book more vividly in the form of audio, video or 3D models, which can increase the interaction and interest, and develop the potential of children and improve learning. The enthusiasm, attention and thinking ability are very helpful.

DRAWINGS

1 is a schematic flow chart of a first embodiment of a digital image processing method according to the present invention;

2 is a schematic flow chart of a second embodiment of a digital image processing method according to the present invention;

3 is a schematic flow chart of a third embodiment of a digital image processing method according to the present invention;

4 is a schematic flow chart of a fourth embodiment of a digital image processing method according to the present invention;

5 is a schematic diagram of functional modules of a first embodiment of a smart early education server according to the present invention;

6 is a schematic diagram of functional modules of a second embodiment of the intelligent early education server of the present invention;

7 is a schematic diagram of functional modules of a first embodiment of a smart early education client according to the present invention;

FIG. 8 is a schematic diagram of functional modules of a second embodiment of a smart early education client according to the present invention.

The implementation, functional features, and advantages of the present invention will be further described in conjunction with the embodiments.

detailed description

It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

The present invention provides a digital image processing method for use in a smart early education server. Referring to FIG. 1, in an embodiment, the method includes:

Step S101, receiving picture data sent by the client;

Among them, the method can be run in a server, and the client is an early education machine.

In this embodiment, the image data in the story book or the textbook can be obtained through the camera of the client, and then the acquired image data is sent to the server, and the server receives the image.

Step S102, extracting feature information of the picture data, and matching the feature information with a tree species feature in a pre-established vocabulary tree;

The server extracts the feature information of the received picture data. In a specific implementation process, the server may extract feature information of the point of interest of the picture data, and the feature information of the point of interest includes color features and edge features of the point of interest. It should be understood that the present embodiment can extract other feature information in addition to the color features and edge features described above.

In this embodiment, a vocabulary tree is established in the server in advance, and the vocabulary tree is established by training the sample picture. In the vocabulary tree, the feature information of each sample picture is represented by a tree species feature, and each sample picture is bound to a multimedia file.

In this embodiment, the feature information of the extracted picture data is matched with the tree type feature in the vocabulary tree. If the matching is successful, the identification information of the sample picture corresponding to the tree species feature that is successfully matched is obtained, and if the matching fails, the client is sent to the client. The end sends a match failure message.

Step S103, when the matching is successful, acquiring a pre-bound multimedia file corresponding to the tree species feature;

In this embodiment, when the feature information of the picture data is successfully matched with the tree type feature in the vocabulary tree, the identification information of the sample picture corresponding to the tree species feature that is successfully matched is obtained, and the identification information of the sample picture can be acquired and bound in advance. Multimedia files.

The multimedia file may be an audio file, a video file, or a multimedia file with a 3D model.

Step S104: Send the multimedia file to the client, so that the client plays.

Compared with the prior art, the embodiment obtains the image data in the storybook or the textbook on the client and sends the image data to the server, and the server matches the feature information of the image data with the tree species feature in the pre-established vocabulary tree to match When successful, the pre-bound multimedia file corresponding to the tree species feature is sent to the client. In this embodiment, the early education machine can be combined with the digital image processing technology, and when the camera of the early education machine acquires the image, the image associated with the image can be played. Multimedia files, the pictures in the book can be more vividly displayed in the form of audio, video or 3D models, which can increase the interactivity and interest. For the development of children's potential, enhance the enthusiasm of learning, attention and thinking ability, etc. Very good help.

In a preferred embodiment, as shown in FIG. 2, on the basis of the foregoing embodiment of FIG. 1, before the step S101, the embodiment further includes:

Step S105, collecting sample picture data;

Step S106, binding each sample picture data with a multimedia file;

Step S107, extracting tree species features of the sample picture data, training the sample picture data according to the tree species characteristics, and establishing a vocabulary tree.

In this embodiment, the sample picture data is recorded on the server in advance, for example, the picture of the main character recorded in the story of "Snow White" or "Ugly Duckling" is used as sample picture data, and each sample picture data is bound to a multimedia file. For example, bind Snow White's sample image data to an audio file, video file, or 3D model with Snow White.

After the sample picture data is bound to the multimedia file, the tree species characteristics of the sample picture data are extracted, the sample picture data is trained according to the tree species characteristics, and the vocabulary tree is established.

The tree species feature is the feature information in the sample picture data. It builds a vocabulary tree that facilitates subsequent queries or matching jobs to quickly query or match relevant information.

The present invention provides a digital image processing method, which is applied to a smart early education client. Referring to FIG. 3, in an embodiment, the method includes:

Step S201: Acquire image data, and send the image data to a smart early education server;

In this embodiment, the image data in the story book or the textbook can be obtained by the camera set on the smart early education client, and the acquired image data is sent to the intelligent early education server.

Step S202, receiving a multimedia file acquired by the smart early education server according to the picture data;

In this embodiment, the server extracts feature information of the received picture data, and specifically extracts feature information of the point of interest of the picture data, and the feature information of the point of interest includes color features and edge features of the point of interest.

Wherein, a vocabulary tree is established in the server in advance, and the vocabulary tree is established by training the sample picture. In the vocabulary tree, the feature information of each sample picture is represented by a tree species feature, and each sample picture is bound to a multimedia file. The feature information of the extracted image data is matched with the tree species feature in the vocabulary tree. If the matching is successful, the identification information of the sample image corresponding to the tree species feature that is successfully matched is obtained, and the identification information of the sample image can be obtained in advance. Bind the multimedia file and send it to the smart early education client.

Step S203, playing the multimedia file.

Compared with the prior art, the embodiment obtains the picture data in the story book or the textbook through the camera set on the smart early education client, and obtains the feature information matched and pre-bound according to the picture data in the intelligent early education server. After the multimedia file, the intelligent early education client receives the multimedia file and plays it, and can display the picture in the book more vividly by means of audio, video or 3D model, which can increase the interaction and interest.

In a preferred embodiment, as shown in FIG. 4, on the basis of the foregoing embodiment of FIG. 3, before the step S203, the embodiment further includes:

Step S204, determining whether the type of the multimedia file is a 3D type, and if it is a 3D type. Step S205 is performed first, and then step S203 is performed. If it is not the 3D type, step S203 is directly executed;

Step S205, performing 3D rendering on the 3D image in the multimedia file.

In this embodiment, the intelligent early education client is combined with the 3D rendering technology. When the type of the multimedia file is 3D type, the intelligent early education client can perform 3D rendering on the 3D model in the media file, such as the picture movement of the story book. Or when rotating, the 3D model performs corresponding movement or rotation at the same time, which can further increase the interest of the early education machine.

The present invention also provides an intelligent early education server. As shown in FIG. 5, an embodiment of the intelligent early education server of the present invention includes:

The receiving module 301 is configured to receive the picture data sent by the client.

The client in this embodiment is an early education machine.

The matching module 302 is configured to extract feature information of the picture data, and match the feature information with a tree species feature in a pre-established vocabulary tree;

The obtaining module 303 is configured to: when the matching is successful, acquire a pre-bound multimedia file corresponding to the tree species feature;

The sending module 304 is configured to send the multimedia file to the client for the client to play.

In a preferred embodiment, as shown in FIG. 6, on the basis of the foregoing embodiment of FIG. 5, the intelligent early education server further includes:

The collecting module 305 is configured to collect sample picture data;

The binding module 306 is configured to bind each sample picture data to a multimedia file;

The establishing module 307 is configured to extract a tree species feature of the sample picture data, train the sample picture data according to the tree species feature, and establish a vocabulary tree.

The present invention also provides an intelligent early education client. As shown in FIG. 7, an embodiment of the intelligent early education client of the present invention includes:

The obtaining module 401 is configured to acquire image data, and send the image data to the intelligent early education server;

The obtaining module 401 of the embodiment may be a camera, and the image data in the story book or the textbook is acquired by the camera set on the smart early education client, and the acquired image data is sent to the intelligent early education server.

The receiving module 402 is configured to receive a multimedia file that is acquired by the smart early education server according to the picture data;

The playing module 403 is configured to play the multimedia file.

In a preferred embodiment, as shown in FIG. 8, on the basis of the foregoing embodiment of FIG. 7, the smart early education client further includes:

The determining module 404 is configured to determine whether the type of the multimedia file is a 3D type;

The rendering module 405 is configured to perform 3D rendering on the multimedia file if the multimedia file is a 3D type.

In this embodiment, the intelligent early education client is combined with the 3D rendering technology. When the type of the multimedia file is a 3D type, the intelligent early education client can perform 3D rendering on the 3D model in the media file, for example, When the picture of the book is moved or rotated, the 3D model performs corresponding movement or rotation at the same time, which can further increase the interest of the early education machine.

The above are only the preferred embodiments of the present invention, and are not intended to limit the scope of the invention, and the equivalent structure or equivalent process transformations made by the description of the present invention and the drawings are directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of the present invention.

Industrial applicability

The invention provides a digital image processing method, an intelligent early education server and a smart early education client, which acquires the image data in the storybook or the textbook on the client and sends the image data to the server, and the server sets the feature information of the image data with the pre-established vocabulary. The characteristics of the tree species in the tree are matched. When the matching is successful, the pre-bound multimedia file corresponding to the tree species feature is sent to the client. The present invention can combine the early education machine with the digital image processing technology, and the camera of the early education machine obtains the image. When playing, the multimedia files related to the picture can be played, and the pictures in the book can be more vividly displayed in the form of audio, video or 3D models, which can increase the interaction and interest, and develop the potential of children and enhance the enthusiasm for learning. , attention and thinking skills are very helpful.

Claims

A digital image processing method is applied to a smart early education server, and the digital image processing method includes:

Receiving picture data sent by the client;

Extracting feature information of the picture data, and matching the feature information with a tree species feature in a pre-established vocabulary tree;

When the matching is successful, acquiring a pre-bound multimedia file corresponding to the tree species feature;

The multimedia file is sent to the client for the client to play.
The digital image processing method according to claim 1, wherein the digital image processing method further comprises: before the step of receiving the image data sent by the client:

Collect sample image data;

Binding each sample image data to a multimedia file;

Extracting tree species features of the sample picture data, training the sample picture data according to the tree species characteristics, and establishing a vocabulary tree.
The digital image processing method according to claim 1, wherein said extracting feature information of said picture data comprises:

Feature information of the point of interest of the picture data is extracted, and the feature information of the point of interest includes a color feature and an edge feature of the point of interest.
A digital image processing method applied to a smart early education client, including:

Obtaining image data, and transmitting the image data to a smart early education server;

Receiving a multimedia file obtained by the smart early education server according to the picture data;

Play the multimedia file.
The digital image processing method according to claim 4, wherein the digital image processing method further comprises: before the step of playing the multimedia file:

Determining whether the type of the multimedia file is a 3D type;

If the multimedia file is a 3D type, the step of performing 3D rendering on the multimedia file is performed first, and then the step of playing the multimedia file is performed.
An intelligent early education server, including:

a receiving module, configured to receive image data sent by the client;

a matching module, configured to extract feature information of the picture data, and match the feature information with a tree species feature in a pre-established vocabulary tree;

Obtaining a module, configured to acquire a pre-bound multimedia file corresponding to the tree species feature when the matching is successful;

The sending module is configured to send the multimedia file to the client for the client to play.
The intelligent early education server according to claim 6, wherein the intelligent early education server further comprises:

The acquisition module is configured to collect sample picture data;

a binding module configured to bind each sample picture data to a multimedia file;

And establishing a module, configured to extract a tree species feature of the sample picture data, train the sample picture data according to the tree species feature, and establish a vocabulary tree.
The smart early education server according to claim 6, wherein the matching module is configured to extract feature information of a point of interest of the picture data, and the feature information of the point of interest includes a color feature and an edge feature of the point of interest.
A smart early education client, including:

Obtaining a module, configured to acquire image data, and send the image data to a smart early education server;

a receiving module, configured to receive a multimedia file acquired by the smart early education server according to the picture data;

a play module, configured to play the multimedia file.
The smart early education client of claim 9, wherein the smart early education client further comprises:

a determining module, configured to determine whether the type of the multimedia file is a 3D type;

And a rendering module, configured to perform 3D rendering on the multimedia file when the multimedia file is a 3D type.