CN111915635A - Test question analysis information generation method and system supporting self-examination paper marking - Google Patents
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- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
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- G06K17/0025—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement consisting of a wireless interrogation device in combination with a device for optically marking the record carrier
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Abstract
The invention provides a test question analysis information generation method supporting self-examination paper marking, which is used for identifying test question information; acquiring storage information of test question analysis information corresponding to the test question information according to the identification result; and generating a two-dimensional code corresponding to the test question analysis information according to the storage information, so that the search difficulty of the test question analysis information is reduced, and the self-examination paper can be read by scanning the two-dimensional code.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a system for generating test question analysis information supporting self-examination paper marking.
Background
The traditional examination paper adopts a full manual mode, and the mode is time-consuming, labor-consuming and low in efficiency. In order to improve the reading efficiency, the machine reading card is widely applied to reading answer sheets, in this way, students firstly fill in the answer of questions to the corresponding positions of the answer sheet by using a 2B pencil, and after the answer sheet is converted into an electronic image by a high-speed scanner, the machine is used for automatically judging whether each objective question is correct or not. The mode of reading answer sheets by machines has the following disadvantages: only the objective questions can be read, and the subjective questions cannot be analyzed.
With the development of information technology, people are not limited to a traditional paper marking mode any more, and can analyze subjective questions by means of multiple tools, for example, answers of test questions are searched by using an internet search tool, and the like. However, this method of searching through the internet sometimes can help users find answers, but has the disadvantage that keywords used by each user based on the understanding of the test questions may be different, the difference of the search is large, and the amount of information of the searched results is huge.
Therefore, how to reduce the difficulty of generating the test question analysis information becomes a problem to be solved urgently.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a system for generating test question analysis information supporting self-examination paper so as to solve the problems of large search difference and huge search result information quantity of the conventional test question analysis information.
In order to solve the above problem, in a first aspect, the present invention provides a method for generating analysis information of test questions, where the method for generating analysis information of test questions supporting self-examination paper reading includes:
identifying test question information;
acquiring storage information of test question analysis information corresponding to the test question information according to the identification result;
and generating a two-dimensional code corresponding to the test question analysis information according to the storage information.
Preferably, before the identifying the test question information, the method further includes:
acquiring a first picture containing test question information;
carrying out gray processing on the first picture containing the test question information to generate a gray image;
carrying out binarization processing on the gray level image to generate a binarized gray level image;
denoising the binarized gray level image;
and carrying out edge detection on the denoised binary gray level image.
Preferably, the obtaining of the first picture containing the test question information includes:
acquiring a first non-reference picture, a reference picture and a second non-reference picture; the first non-reference picture, the reference picture and the second non-reference picture are pictures containing the same test question information, and the exposure duration is sequentially increased;
and processing the first non-reference picture, the reference picture and the second non-reference picture to generate a first picture.
Preferably, the generating a two-dimensional code corresponding to the test question analysis information according to the storage information includes:
and combining the first storage information of the test question information with the second storage information of the test question information similar to the test question information to generate the two-dimensional code.
In a second aspect, the present invention provides a self-examination-supporting test question analysis information generation system, comprising:
the identification unit is used for identifying the test question information;
the acquisition unit is used for acquiring the storage information of the test question analysis information corresponding to the test question information according to the identification result;
and the generating unit is used for generating a two-dimensional code corresponding to the test question analysis information according to the storage information.
Preferably, the obtaining unit is further configured to obtain a first picture containing test question information;
the generating unit is further used for carrying out gray processing on the first picture containing the test question information to generate a gray image;
the generating unit is also used for carrying out binarization processing on the gray level image to generate a binarized gray level image;
the processing unit is used for carrying out denoising processing on the binarized gray level image;
the processing unit is further configured to perform edge detection on the denoised binary grayscale image.
Preferably, the obtaining unit is specifically configured to obtain a first non-reference picture, a reference picture, and a second non-reference picture; the first non-reference picture, the reference picture and the second non-reference picture are pictures containing the same test question information, and the exposure duration is sequentially increased;
the processing unit is further configured to process the first non-reference picture, the reference picture, and the second non-reference picture to generate a first picture.
Preferably, the generating unit is specifically configured to combine the first storage information of the test question information with the second storage information of the test question information similar to the test question information to generate the two-dimensional code.
Therefore, the test question information is identified by applying the test question analysis information generation method supporting self-examination paper provided by the invention; acquiring storage information of test question analysis information corresponding to the test question information according to the identification result; and generating a two-dimensional code corresponding to the test question analysis information according to the storage information, so that the search difficulty of the test question analysis information is reduced, and automatic paper marking can be realized by scanning the two-dimensional code.
Drawings
Fig. 1 is a flowchart of a method for generating test question analysis information supporting self-examination paper marking according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for processing test question information according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a test question analysis information generation system supporting self-examination paper reading according to an embodiment of the present invention.
Detailed Description
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Fig. 1 is a flowchart of a method for generating test question analysis information supporting self-examination paper marking according to an embodiment of the present invention. The execution main body of the method can be a terminal, a test question analysis information generation system supporting self-examination paper marking, and the like. As shown in fig. 1, the method comprises the steps of:
and step 110, identifying the test question information.
The picture of the test paper containing the test question information can be obtained from the database, and the picture containing the test question information can also be shot through the terminal. When the latter mode is selected, the terminal may be equipped with an app for shooting test question information, a picture containing the test question information is obtained by pressing a shooting key of the app, then the test question information may be changed by stretching the range of the selection box, for example, three test questions exist in the shot picture, one or two of the three test questions may be selected by pulling the selection box, and then a confirmation key on the app is clicked, where the confirmation key may be "confirm", or "OK", or "check mark", and the present application is not limited thereto.
In the application, the photographing mode is not limited, and the photographing mode can be horizontal photographing or vertical photographing.
And step 120, acquiring storage information of the test question analysis information corresponding to the test question information according to the identification result.
Specifically, after the background server receives the uploaded picture, the content of the test questions contained in the picture is identified, corresponding test question information is extracted, the identification process can be realized by using image identification, after image characteristics are extracted, the test question information can be identified according to the image characteristics, and test question analysis information, namely answers, corresponding to the test questions can be searched from the question bank database.
And step 130, generating a two-dimensional code corresponding to the test question analysis information according to the storage information.
The two-dimensional code technology is characterized by that it uses a certain specific geometric figure and black-white alternative figure distributed on the plane (two-dimensional direction) according to a certain rule to record data symbol information, and utilizes the concept of "0" and "1" bit stream forming internal logic basis of computer to make code production, and uses several geometric forms correspondent to binary system to represent literal numerical value information, and utilizes image input equipment or photoelectric scanning equipment to automatically read and implement automatic information processing. The technology is widely applied to industries such as catering, supermarkets, movies, shopping, traveling, automobiles and the like in the prior art.
Therefore, after the two-dimensional code is generated from the stored information, the stored information of the test question analysis information corresponding to the test question information can be acquired by scanning the two-dimensional code on the test question, and the self-examination function is realized.
As for step 110, before step 110, the method further includes a step that after a first picture containing the test question information is obtained, the terminal may further process the first picture, as shown in fig. 2, and fig. 2 is a flowchart of a test question information processing method provided in an embodiment of the present invention. The processing method comprises the following steps:
Where a grayscale image represents an image with only one sample color per pixel, typically displayed as a grayscale from the darkest black to the brightest white.
How to obtain the first picture containing the test question information is described in detail as follows:
firstly, three pictures containing test question information can be acquired, and the three pictures comprise: a first non-reference picture, a reference picture, and a second non-reference picture; the first non-reference picture, the reference picture and the second non-reference picture are pictures containing the same test question information, and the exposure duration is sequentially increased. Therefore, at least three pictures related to the test question information are acquired, and the problem of picture blurring caused by hand shaking or the influence of the external environment is avoided.
And secondly, processing the first non-reference picture, the reference picture and the second non-reference picture to generate a first picture.
Specifically, the RGB maps of the first non-reference image, the reference image, and the second non-reference image are converted into grayscale maps, respectively. And performing HM on a brightness channel, performing HM on the gray scale map of the first non-reference image by taking the gray scale map of the reference image as a standard, turning up the gray scale map of the first non-reference image, performing histogram matching on the gray scale map of the second non-reference image, and turning down the gray scale map of the second non-reference image. Finally, comparing the gray value difference between the gray level image of the first non-reference image after the brightness adjustment and the gray level image of the reference image, determining all the pixels with the gray level difference larger than the preset threshold value as the first motion area, correspondingly, comparing the gray value difference between the gray level image of the second non-reference image after the brightness adjustment and the gray level image of the reference image, determining all the pixels with the gray level difference larger than the preset threshold value as the second motion area, for example, the gray value of the first pixel in the gray level image of the second non-reference image after the brightness adjustment is 200, the gray value of the first pixel in the gray level image of the reference image is 100, and the gray value difference between the two is 100, and when the preset threshold is 50, the difference between the gray values of the two is larger than the preset threshold, so that the pixel value of the first pixel point is 1, and after all the pixel points with the pixel values of 1 are obtained, the dried second motion area is obtained through threshold filtering and corrosion expansion operation.
Secondly, determining a target motion area according to a comparison result between the first proportion and a second threshold value and a comparison result between the second proportion and the second threshold value.
The first proportion is the proportion occupied by the first motion area in the first non-reference image, the second proportion is the proportion occupied by the second motion area in the second non-reference image, and the target motion area comprises at least one connected area.
And finally, obtaining a first HDR image according to the first weight value and the second weight value.
The first weighted value is the sum of the product of the saturation, the contrast and the exposure degree of each pixel point in the first non-reference image and the product of the saturation, the contrast and the exposure degree of each pixel point in the second non-reference image; or, the first weight value is a product of saturation, contrast and exposure of each pixel point in the first non-reference image; or, the first weight value is a product of saturation, contrast and exposure of each pixel point in the second non-reference image; the second weight value is the product of the saturation, the contrast and the exposure degree of each pixel point in the reference image.
The first proportion is the proportion of a first motion area in the first non-reference image, the second proportion is the proportion of a second motion area in the second non-reference image, and the target motion area comprises at least one connected area. In the field of image processing, a Connected Component generally refers to an image region composed of foreground pixels having the same pixel value and located adjacent to each other in an image.
Further, determining the target motion region according to a comparison result between the first proportion and a first threshold and a comparison result between the second proportion and the first threshold, including:
when the first proportion and the second proportion are not larger than the first threshold value, overlapping the first motion area and the second motion area, and determining the overlapped area as a target motion area; alternatively, the first and second electrodes may be,
when the first ratio is not larger than the first threshold value and the second ratio is larger than the first threshold value, determining that the first motion area is a target motion area; alternatively, the first and second electrodes may be,
and when the first ratio is larger than a first threshold value and the second ratio is not larger than the first threshold value, determining the second motion area as a target motion area.
And step 220, performing binarization processing on the gray level image to generate a binarized gray level image.
And step 230, denoising the binarized grayscale image.
The binarization processing can be performed by using an Otsu algorithm, some noise appears in the gray level image after the binarization processing, for noise removal in the image, an eight-neighborhood search algorithm can be adopted to calculate the area of a connected region (the connected region generally refers to an image region which has the same pixel value and is formed by adjacent foreground pixel points in the image), and if the area of some connected regions is less than 8 pixels, the connected regions are considered as noise and are removed.
And step 240, performing edge detection on the denoised binary gray level image.
The terminal can carry out edge detection on the picture and identify the edge of the text content contained in the picture so as to further narrow the identification range and more accurately position the test question analysis information corresponding to the test question information.
After the test question information is identified, the identified test question information can be uploaded to the server, so that the test question information can be searched in a question bank of the server, the storage information, such as a storage address, of the test question analysis information is determined, and the two-dimensional code is generated according to the storage information of the test question analysis information.
In addition, the server of the terminal may search the question bank of the database for question analysis information similar (different but similar) to the photographed question information picture, and include the stored information of the question analysis information in the two-dimensional code, thereby consolidating the question knowledge point.
The two-dimensional code can be generated by the storage information of the test question analysis information of each test question information independently, so that the test question analysis information of similar test questions can be known conveniently by scanning the two-dimensional code, and therefore, knowledge points can be better mastered. The storage information of the analysis information of the test questions of one test paper can be generated into a two-dimensional code, so that the storage information of the analysis information of the test questions of all the test papers can be conveniently acquired at one time, and the operation is convenient. The number of the two-dimensional codes is not limited in the present application.
Therefore, the test question information is identified by applying the test question analysis information generation method supporting self-examination paper provided by the invention; acquiring storage information of test question analysis information corresponding to the test question information according to the identification result; and generating a two-dimensional code corresponding to the test question analysis information according to the storage information, so that the generation difficulty of the test question analysis information is reduced, and the self-examination paper reading can be realized by scanning the two-dimensional code only by generating the two-dimensional code, so that the examination paper reading is more convenient.
Fig. 3 is a schematic structural diagram of a test question analysis information generation system supporting self-examination paper reading according to an embodiment of the present invention. As shown in fig. 3, the self-examination-supporting test question parsing information generating system 300 includes a recognition unit 310, an acquisition unit 320, and a generation unit 330.
The recognition unit 310 is used for recognizing the test question information.
The obtaining unit 320 is configured to obtain storage information of the test question analysis information corresponding to the test question information according to the identification result.
The generating unit 330 is configured to generate a two-dimensional code corresponding to the test question analysis information according to the storage information.
Further, the obtaining unit is further configured to obtain a first picture containing test question information;
the generating unit is further used for carrying out gray processing on the first picture containing the test question information to generate a gray image;
the generating unit is also used for carrying out binarization processing on the gray level image to generate a binarized gray level image;
the processing unit is used for carrying out denoising processing on the binarized gray level image;
the processing unit is further configured to perform edge detection on the denoised binary grayscale image.
Further, the obtaining unit is specifically configured to obtain a first non-reference picture, a reference picture, and a second non-reference picture; the first non-reference picture, the reference picture and the second non-reference picture are pictures containing the same test question information, and the exposure duration is sequentially increased;
the processing unit is further configured to process the first non-reference picture, the reference picture, and the second non-reference picture to generate a first picture.
Further, the generating unit is specifically configured to combine the first storage information of the test question information and the second storage information of the test question information similar to the test question information to generate the two-dimensional code.
Therefore, by applying the test question analysis information generation system supporting self-examination paper marking provided by the embodiment of the invention, the identification unit identifies the test question information; the acquisition unit acquires the storage information of the test question analysis information corresponding to the test question information according to the identification result; and the generating unit generates a two-dimensional code corresponding to the test question analysis information according to the storage information. The search difficulty of test question analysis information is reduced, and self-examination paper reading can be realized by scanning the two-dimensional code.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, it should be understood that the above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A method for generating test question analysis information supporting self-examination paper is characterized by comprising the following steps:
identifying test question information;
acquiring storage information of test question analysis information corresponding to the test question information according to the identification result;
and generating a two-dimensional code corresponding to the test question analysis information according to the storage information.
2. The method for generating test question parsing information supporting self-scoring as recited in claim 1, wherein before the test question information is identified, the method further comprises:
acquiring a first picture containing test question information;
carrying out gray processing on the first picture containing the test question information to generate a gray image;
carrying out binarization processing on the gray level image to generate a binarized gray level image;
denoising the binarized gray level image;
and carrying out edge detection on the denoised binary gray level image.
3. The method for generating test question parsing information supporting self-scoring as recited in claim 2, wherein the obtaining of the first picture containing test question information comprises:
acquiring a first non-reference picture, a reference picture and a second non-reference picture; the first non-reference picture, the reference picture and the second non-reference picture are pictures containing the same test question information, and the exposure duration is sequentially increased;
and processing the first non-reference picture, the reference picture and the second non-reference picture to generate a first picture.
4. The method for generating test question analysis information supporting self-scoring according to claim 1, wherein generating a two-dimensional code corresponding to the test question analysis information according to the storage information includes:
and combining the first storage information of the test question information with the second storage information of the test question information similar to the test question information to generate the two-dimensional code.
5. A self-examination-paper-reading-supported test question analysis information generation system is characterized by comprising:
the identification unit is used for identifying the test question information;
the acquisition unit is used for acquiring the storage information of the test question analysis information corresponding to the test question information according to the identification result;
and the generating unit is used for generating a two-dimensional code corresponding to the test question analysis information according to the storage information.
6. The system for generating test question parsing information supporting self-scoring according to claim 5, wherein the obtaining unit is further configured to obtain a first picture containing test question information;
the generating unit is further used for carrying out gray processing on the first picture containing the test question information to generate a gray image;
the generating unit is also used for carrying out binarization processing on the gray level image to generate a binarized gray level image;
the processing unit is used for carrying out denoising processing on the binarized gray level image;
the processing unit is further configured to perform edge detection on the denoised binary grayscale image.
7. The system for generating test question parsing information supporting self-scoring according to claim 6, wherein the obtaining unit is specifically configured to obtain a first non-reference picture, a reference picture and a second non-reference picture; the first non-reference picture, the reference picture and the second non-reference picture are pictures containing the same test question information, and the exposure duration is sequentially increased;
the processing unit is further configured to process the first non-reference picture, the reference picture, and the second non-reference picture to generate a first picture.
8. The system of claim 5, wherein the generating unit is specifically configured to combine first stored information of the test question information with second stored information of test question information similar to the test question information to generate a two-dimensional code.
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| CN113705509A (en) * | 2021-09-02 | 2021-11-26 | 北京云蝶智学科技有限公司 | Method and device for acquiring analysis information of test questions |
| CN113723539A (en) * | 2021-09-02 | 2021-11-30 | 北京云蝶智学科技有限公司 | Test question information acquisition method and device |
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