CN114155382A

CN114155382A - Image processing method and server based on artificial intelligence

Info

Publication number: CN114155382A
Application number: CN202111536934.3A
Authority: CN
Inventors: 陈志明
Original assignee: Changshu Youle Intelligent Technology Co ltd
Current assignee: Changshu Youle Intelligent Technology Co ltd
Priority date: 2021-12-16
Filing date: 2021-12-16
Publication date: 2022-03-08

Abstract

The disclosure provides an image processing method and a server based on artificial intelligence, and only rough designated labels corresponding to image feature contents are analyzed, so that the analysis efficiency can be improved, and the analysis accuracy can be improved. In addition, the matching condition generated in the embodiment of the application has the characteristic contents of the image appearing for many times, so that too many resources are not wasted in the matching condition.

Description

Image processing method and server based on artificial intelligence

Technical Field

The present application relates to the field of artificial intelligence and image processing technologies, and in particular, to an image processing method and a server based on artificial intelligence.

Background

With the continuous development of science and technology, the processing functions of various data information are more and more diversified. Taking image processing as an example, in order to meet various requirements, fine analysis processing is usually implemented in current image processing, but this may cause reduction in analysis efficiency and waste of resources.

Disclosure of Invention

In order to solve the technical problems in the related art, the application provides an image processing method and a server based on artificial intelligence.

The application provides an image processing method based on artificial intelligence, which comprises the following steps: acquiring image information by optimizing an image processing thread; generating a matching condition of image characteristic content included in the image information and the designated label based on the optimized image information; and carrying out image analysis by combining the generated designated label corresponding to the image characteristic content in the matching condition.

Preferably, the matching of the image feature content included in the generated image information and the specified label includes:

in the characteristic analysis process of the image processing thread, processing the analyzed video to be processed according to the image information obtained by optimization to obtain the image characteristic content in the video to be processed; allocating a designated label for each image characteristic content in the obtained video to be processed; and analyzing the matching condition of each image characteristic content in the video to be processed and the appointed label thereof.

Preferably, the processing the analyzed video to be processed based on the image information obtained by optimization includes:

and mining image characteristic content consistent with the image characteristic content in the image information obtained in the optimization process from the image information in the video to be processed by contrasting the image information obtained by optimization and the image information in the video to be processed, wherein the mined image characteristic content is the image characteristic content in the obtained video to be processed.

in the starting of the image processing thread, identifying the index of the information segment in the image information obtained from the image operation terminal as the designated label of the image characteristic content included in the image information; and generating the matching condition of the image characteristic content included in the image information and the specified label.

Preferably, the image analysis performed by combining the specified labels corresponding to the image feature contents in the generated matching condition includes:

and adjusting the information segment in the image information obtained from the image operation end to be matched with the video to be processed by the corresponding specified label in combination with the generated matching condition during the starting of the image processing thread.

Preferably, the method further comprises: and during image analysis, changing the specific label to be analyzed into image characteristic content in combination with the generated matching condition.

The embodiment of the application also provides an image processing server, which comprises a memory, a processor and a network module; wherein the memory, the processor, and the network module are electrically connected directly or indirectly; the processor reads the computer program from the memory and runs the computer program to realize the method.

The technical scheme provided by the embodiment of the application can have the following beneficial effects.

When the image is analyzed, only the rough designated label corresponding to the image characteristic content is analyzed, so that the analysis efficiency can be improved, and meanwhile, the analysis accuracy can be improved. In addition, the matching condition generated in the embodiment of the application has the characteristic contents of the image appearing for many times, so that too many resources are not wasted in the matching condition.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.

Fig. 1 is a flowchart of an artificial intelligence based image processing method according to an embodiment of the present application.

Fig. 2 is a schematic diagram of a hardware structure of an image processing server according to an embodiment of the present application.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

Referring to fig. 1, an embodiment of the present application provides a flowchart of an artificial intelligence-based image processing method, which is applied to an image processing server, and further, the method may specifically include the following steps 11 to 13.

And 11, acquiring image information through optimization of the image processing thread.

And 12, generating the matching condition of the image characteristic content included in the image information and the designated label based on the optimized image information.

In an example, the matching between the image feature content included in the generated image information and the specified label described above may specifically include the content recorded in the following steps 121 to 123.

And step 121, in the characteristic analysis process of the image processing thread, processing the analyzed video to be processed according to the optimized image information to obtain image characteristic content in the video to be processed.

And step 122, assigning a designated label to each image characteristic content in the obtained video to be processed.

In an example, the processing the analyzed video to be processed based on the recorded image information obtained by optimization specifically includes: and mining image characteristic content consistent with the image characteristic content in the image information obtained in the optimization process from the image information in the video to be processed by contrasting the image information obtained by optimization and the image information in the video to be processed, wherein the mined image characteristic content is the image characteristic content in the obtained video to be processed.

And 123, analyzing the matching condition of each image characteristic content in the video to be processed and the appointed label thereof.

In an example, the matching between the image feature content included in the recorded generated image information and the specified label may specifically include the following: in the starting of the image processing thread, identifying the index of the information segment in the image information obtained from the image operation terminal as the designated label of the image characteristic content included in the image information; and generating the matching condition of the image characteristic content included in the image information and the specified label.

And step 13, combining the generated appointed label corresponding to the image characteristic content in the matching condition to perform image analysis.

In an example, the image analysis performed on the specified label corresponding to the image feature content in the matching condition generated by the combining may specifically include the following: and adjusting the information segment in the image information obtained from the image operation end to be matched with the video to be processed by the corresponding specified label in combination with the generated matching condition during the starting of the image processing thread.

In one example, the image processing method may further include: and during image analysis, changing the specific label to be analyzed into image characteristic content in combination with the generated matching condition.

On the basis, please refer to fig. 2 in combination, the present application further provides a schematic diagram of a hardware structure of the image processing server 20, which specifically includes a memory 21, a processor 22, a network module 23, and an image processing apparatus. The memory 21, the processor 22 and the network module 23 are electrically connected directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 21 stores therein an image processing apparatus including at least one software functional module which may be stored in the memory 21 in the form of software or firmware (firmware), and the processor 22 executes software programs and modules stored in the memory 21.

The Memory 21 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 21 is configured to store a program, and the processor 22 executes the program after receiving the execution instruction.

The processor 22 may be an integrated circuit chip having data processing capabilities. The Processor 22 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like. The various methods, steps and logic blocks disclosed in embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The network module 23 is used for establishing a communication connection between the image processing server 20 and other communication terminal devices through a network, so as to implement transceiving operation of network signals and data. The network signal may include a wireless signal or a wired signal.

Further, a readable storage medium is provided, on which a program is stored, which when executed by a processor implements the method described above.

It will be understood that the present application is not limited to the precise arrangements 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 application is limited only by the appended claims.

It is well known to those skilled in the art that with the development of electronic information technology such as large scale integrated circuit technology and the trend of software hardware, it has been difficult to clearly divide the software and hardware boundaries of a computer system. As any of the operations may be implemented in software or hardware. Execution of any of the instructions may be performed by hardware, as well as by software. Whether a hardware implementation or a software implementation is employed for a certain machine function depends on non-technical factors such as price, speed, reliability, storage capacity, change period, and the like. Accordingly, it will be apparent to those skilled in the art of electronic information technology that a more direct and clear description of one embodiment is provided by describing the various operations within the embodiment. Knowing the operations to be performed, the skilled person can directly design the desired product based on considerations of said non-technical factors.

The present application may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present application.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present application may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry can execute computer-readable program instructions to implement aspects of the present application by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).

Various aspects of the present application are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, by software, and by a combination of software and hardware are equivalent.

Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the application is defined by the appended claims.

Claims

1. An image processing method based on artificial intelligence, comprising:

acquiring image information by optimizing an image processing thread; generating a matching condition of image characteristic content included in the image information and the designated label based on the optimized image information; and carrying out image analysis by combining the generated designated label corresponding to the image characteristic content in the matching condition.

2. The artificial intelligence based image processing method according to claim 1, wherein the generating image information includes matching image feature content with a specified label, including:

3. The artificial intelligence based image processing method according to claim 2, wherein the processing the analyzed video to be processed based on the optimized image information comprises:

4. The artificial intelligence based image processing method according to claim 1, wherein the generating image information includes matching image feature content with a specified label, including:

5. The artificial intelligence based image processing method according to claim 1, wherein the image analysis performed in combination with the specified label corresponding to the image feature content in the generated matching condition includes:

6. The artificial intelligence based image processing method according to any one of claims 1-5, wherein the method further comprises: and during image analysis, changing the specific label to be analyzed into image characteristic content in combination with the generated matching condition.

7. An image processing server, comprising a memory, a processor and a network module; wherein the memory, the processor, and the network module are electrically connected directly or indirectly; the processor implements the method of any one of claims 1-6 by reading the computer program from the memory and running it.