Paleontological fossil standard database thematic service system

Abstract

The invention discloses an ancient organism fossil standard database thematic service system, and relates to the technical field of electric digital data processing. The paleontology fossil standard database thematic service system comprises an information input module, a feature extraction module, an image processing module and a retrieval output module. The fossil region integrity is analyzed according to the fossil retrieval image, whether fossil retrieval image feature extraction is carried out is judged, and whether fossil retrieval image processing adjustment is carried out is analyzed after fossil retrieval image feature extraction is carried out. After the fossil retrieval image is processed and adjusted, retrieval is performed according to the obtained fossil retrieval image features and the retrieval text to obtain the retrieval information, so that the retrieval information is analyzed and judged whether to output the retrieval information or not, and the retrieval effectiveness of the paleontological fossil standard database is improved. The problem that in the prior art, retrieval results provided by a paleontology fossil standard database are not accurate is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and particularly to a special service system for a standard database of paleontological fossils. Background Art

[0002] Paleontology, as an important discipline for studying the evolutionary history of life on Earth, mainly relies on fossils for its research materials. However, paleontological fossils are diverse in variety, large in quantity, and widely distributed, which poses great challenges to the management, query, and utilization of fossil materials. The traditional management methods of fossil materials mainly rely on paper documents and physical specimens, suffering from problems such as low retrieval efficiency and difficult information sharing. With the rapid development of computer technology and information technology, database technology has gradually become an important means for fossil material management. The special service system for the standard database of paleontological fossils has emerged as the times require. It uses advanced database technology to digitally store, manage, and query fossil materials, greatly improving the utilization efficiency and sharing degree of fossil materials.

[0003] Currently, the special service system for the standard database of paleontological fossils has made remarkable progress. For example, the special service system for the standard database of paleontological fossils developed by the Institute of Geology, Chinese Academy of Geological Sciences is one of the relatively well-known paleontological fossil databases in China. This system not only provides rich fossil text information but also contains a large amount of fossil retrieval image data. Users can conduct retrievals in two ways: by text and by image. In addition, this system has realized the visual display of the geographical location of fossils, geological age, paleogeographical location, etc., providing users with a more intuitive and convenient query experience.

[0004] In addition to the above-mentioned system, there are also many other types of paleontological fossil databases at home and abroad. These databases have their own characteristics in terms of data collation methods, online functions, etc. For example, some databases are built based on fossil specimens or fossil retrieval images, mainly providing services such as cataloging, querying, online browsing, and physical borrowing of the fossil specimens in the collection; while some other databases are built based on research objects such as fossil occurrence records, localities, or geological profiles, mainly serving scientific research workers on the front line of scientific research.

[0005] However, there are some problems in the process of retrieval through the database system, resulting in inaccurate retrieval results. Therefore, a more accurate database retrieval method is needed.

[0006] The existing paleontological fossil database system conducts relevant retrievals by retrieving text and images to obtain retrieval results, and outputs the retrieval results to implement the retrieval function of the paleontological fossil database system.

[0007] For example, a three-dimensional modeling database service platform for important geological drilling data disclosed in the patent application with the publication number: CN118193611A includes: a data quality inspection module that inspects the submitted drilling data in each region, stores the data that passes the inspection into the drilling database, and stores the data that fails the inspection into the drilling database after parsing; a data management module that classifies the data in the drilling database by level for retrieval by users with different permissions, and also updates the data in the drilling database; a data modeling module that performs three-dimensional modeling on the drilling data; a data service module that publishes the drilling data in the form of a three-dimensional model; a drilling data retrieval module that provides users with the functions of retrieving and displaying the published data; a special product module that provides users with the functions of retrieving and displaying special products associated with the drilling; and a data statistics module that displays the statistical results of the drilling data under various statistical classifications for users.

[0008] For example, a patent information processing service system and its service method based on word frequency disclosed in the patent application with the publication number: CN114266243A includes: a dedicated memory, an automatic warehousing module, an association matching module, a special data service module, a technology supply and demand matching module, and an auxiliary decision-making module for patent license evaluation. The dedicated memory is used to store the substitute word library, and the automatic warehousing module is used to establish the substitute word library and obtain a standardized retrieval program, and retrieve the first patent information in the full-field patent database according to the words in the substitute word library as keywords within the first time interval.

[0009] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0010] In the prior art, in the process of retrieving according to the input text and image through the special service system of the paleontological fossil standard database, since the quality of the input image and the detail level of the text will affect the accuracy of the retrieval result, there is a problem that the retrieval result provided by the paleontological fossil standard database is inaccurate. Summary of the Invention

[0011] By providing a special service system for the paleontological fossil standard database in the embodiments of the present application, the problem that the retrieval result provided by the paleontological fossil standard database in the prior art is inaccurate is solved, and the retrieval effectiveness of the paleontological fossil standard database is improved.

[0012] An embodiment of the present application provides a special service system for a paleontological fossil standard database, including: an information input module, a feature extraction module, an image processing module, and a retrieval output module; wherein, the information input module: is used to input a fossil retrieval image and retrieval text into the paleontological fossil standard database; the feature extraction module: is used to analyze the integrity of the fossil area based on the fossil retrieval image and determine whether to extract the features of the fossil retrieval image; the image processing module: is used to analyze whether to adjust the fossil retrieval image processing after extracting the features of the fossil retrieval image; the retrieval output module: is used to retrieve the retrieval information based on the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing is adjusted, and analyze the retrieval information to determine whether to output the retrieval information.

[0013] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0014] 1. By inputting a fossil retrieval image and retrieval text into the paleontological fossil standard database, analyzing the integrity of the fossil area based on the fossil retrieval image and determining whether to extract the features of the fossil retrieval image, analyzing whether to adjust the fossil retrieval image processing after extracting the features of the fossil retrieval image, retrieving the retrieval information based on the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing is adjusted, and analyzing the retrieval information to determine whether to output the retrieval information, the retrieval information with high content accuracy is output as the retrieval result, thereby improving the retrieval effectiveness of the paleontological fossil standard database and effectively solving the problem that the retrieval results provided by the paleontological fossil standard database in the prior art are inaccurate.

[0015] 2. By obtaining the fossil area integrity data from the fossil retrieval image, quantifying the integrity degree of the area according to the fossil area integrity data, obtaining the fossil area integrity evaluation value, and thus determining whether to extract the features of the fossil retrieval image based on the fossil area integrity, more comprehensive fossil features are obtained after extracting the features according to the fossil retrieval image with qualified integrity.

[0016] 3. By obtaining the fossil area feature extraction effect data after extracting the features of the fossil retrieval image, quantifying the fossil area feature extraction effect according to the fossil area feature extraction effect data, obtaining the fossil area feature extraction effect evaluation value, and determining whether to adjust the fossil retrieval image processing according to the fossil area feature extraction effect evaluation value, so as to extract the features of the fossil retrieval image after the fossil retrieval image processing is adjusted, and thus the fossil features with significantly improved feature extraction effect, more representativeness and distinctiveness are obtained.

[0017] 4. Obtain the retrieval result matching data based on the retrieval information and the retrieval text, analyze the retrieval result matching degree based on the retrieval result matching data, analyze the content matching degree of the retrieval information based on the retrieval result matching degree, and perform retrieval output feedback based on the content matching degree of the retrieval information, so as to obtain a more accurate retrieval output result through the special service system of the paleontological fossil standard database. Brief Description of the Drawings

[0018] Figure 1 It is a schematic structural diagram of a special service system of a paleontological fossil standard database provided by an embodiment of the present application. Detailed Embodiment

[0019] The embodiment of the present application provides a special service system of a paleontological fossil standard database, which solves the problem that the retrieval results provided by the existing paleontological fossil standard database are inaccurate. By inputting the fossil retrieval image and the retrieval text into the paleontological fossil standard database, analyze the integrity of the fossil area according to the fossil retrieval image and judge whether to extract the features of the fossil retrieval image. After extracting the features of the fossil retrieval image, analyze whether to adjust the processing of the fossil retrieval image. After adjusting the processing of the fossil retrieval image, perform a retrieval to obtain the retrieval information based on the obtained fossil retrieval image features and the retrieval text, analyze the retrieval information to judge whether to output the retrieval information, and thus output the retrieval information with high content accuracy as the retrieval result, realizing the improvement of the retrieval effectiveness of the paleontological fossil standard database.

[0020] The technical solution in the embodiment of the present application is to solve the problem that the retrieval results provided by the above-mentioned paleontological fossil standard database are inaccurate, and the general idea is as follows:

[0021] By inputting the fossil retrieval image and retrieval text into the paleontological fossil standard database, obtaining the fossil area integrity data from the fossil retrieval image, quantifying the integrity degree of the area according to the fossil area integrity data to obtain the fossil area integrity evaluation value, thereby judging whether to perform fossil retrieval image feature extraction based on the fossil area integrity evaluation value, obtaining the fossil area feature extraction effect data after performing fossil retrieval image feature extraction, quantifying the fossil area feature extraction effect according to the fossil area feature extraction effect data to obtain the fossil area feature extraction effect evaluation value, judging whether to perform fossil retrieval image processing adjustment based on the fossil area feature extraction effect evaluation value, performing retrieval to obtain retrieval information according to the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing adjustment, obtaining the retrieval result matching data according to the retrieval information and the retrieval text, analyzing the retrieval result matching degree according to the retrieval result matching data, analyzing the content matching degree of the retrieval information according to the retrieval result matching degree, performing retrieval output feedback according to the content matching degree of the retrieval information, and outputting the retrieval information with high content accuracy as the retrieval result, achieving the effect of improving the retrieval effectiveness of the paleontological fossil standard database.

[0022] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the specification drawings and specific embodiments.

[0023] As Figure 1 shown, it is a schematic structural diagram of a special service system for a paleontological fossil standard database provided by an embodiment of the present application. The special service system for a paleontological fossil standard database provided by an embodiment of the present application includes: an information input module, a feature extraction module, an image processing module, and a retrieval output module; wherein, the information input module: is used to input the fossil retrieval image and retrieval text into the paleontological fossil standard database; the feature extraction module: is used to analyze the integrity of the fossil area according to the fossil retrieval image and judge whether to perform fossil retrieval image feature extraction; the image processing module: is used to analyze whether to perform fossil retrieval image processing adjustment after performing fossil retrieval image feature extraction; the retrieval output module: is used to perform retrieval to obtain retrieval information according to the obtained fossil retrieval image features and retrieval text after the fossil retrieval image processing adjustment, and analyze the retrieval information to judge whether to output the retrieval information.

[0024] Furthermore, the specific analysis process for analyzing the integrity of the fossil area based on the fossil retrieval image is as follows: Obtain the fossil area integrity data from the fossil retrieval image; the fossil area integrity data includes: the intersection area of the fossil areas, the union area of the fossil areas, the area of the fossil areas, the length of the fossil contour breaks, the number of fossil contour breaks, and the standard deviation of the fossil contour curvature; Quantify the integrity degree of the area based on the fossil area integrity data to obtain the fossil area integrity evaluation value, which is used to quantitatively analyze the integrity of the fossil area in the fossil retrieval image; Compare the fossil area integrity evaluation value with the preset fossil area integrity threshold obtained from the database. When the fossil area integrity evaluation value is less than the preset fossil area integrity threshold obtained from the database, it indicates that the integrity of the fossil area is unqualified; in other cases, it indicates that the integrity of the fossil area is qualified; The specific analysis process for determining whether to extract the features of the fossil retrieval image is as follows: When the integrity of the fossil area is qualified, extract the features of the fossil retrieval image; when the integrity of the fossil area is unqualified, do not extract the features of the fossil retrieval image, prompt the user to re-enter the fossil retrieval image, and when the integrity of the fossil area of the monitored fossil retrieval image is qualified, extract the features of the fossil retrieval image.

[0025] In this embodiment, the fossil area in the fossil retrieval image is separated from the background area through an image segmentation algorithm (such as threshold segmentation, region growing, edge detection, etc.) to obtain the fossil area. The image registration technology is used to align the standardized fossil template with the segmented fossil area to ensure that the standardized fossil template and the fossil area are consistent in position and angle. After alignment, calculate the intersection area between the fossil area and the standardized fossil template. This area reflects the common part between the two, that is, the intersection area of the fossil areas, unit: square pixels. Similarly, obtain the union area of the fossil area and the standardized complete fossil template, that is, the total area covered by the two, that is, the union area of the fossil areas, unit: square pixels. The ratio of the intersection area to the union area represents the overlap degree, and the value of the overlap degree is between 0 and 1, where: an overlap degree of 1 means that the segmented fossil area completely coincides with the standardized template without missing or being blocked; the closer the overlap degree is to 0, the smaller the overlap between the fossil area and the standardized template, and the greater the possible missing or occlusion.

[0026] The area of the fossil area obtained through image segmentation, that is, the fossil area area, unit: square pixels. Obtain the expected area estimated based on the standardized complete fossil template from the database, that is, the minimum complete fossil area, unit: square pixels. The ratio of the fossil area area to the minimum complete fossil area represents the integrity of the fossil. The smaller the ratio, the lower the preservation integrity of the fossil, and the more likely there are missing or broken parts.

[0027] Use edge detection algorithms (such as Canny edge detection) to process fossil retrieval images and extract the contours of fossils. Edge detection algorithms can identify brightness changes in images and mark these changes as edges to obtain the contours of fossils. On the extracted contours, identify broken or discontinuous parts. This can be achieved by observing the continuity of the contours. If there are gaps or jumps on the contours, it indicates that there are breaks. For each identified broken part, calculate its length. The break length can be obtained by calculating the distance between the two end points of the broken part. If the broken part is composed of multiple line segments, it is necessary to calculate the length of each line segment separately and sum them to obtain the fossil contour break length, unit: pixel. Count the total number of broken parts on the contour to obtain the number of fossil contour breaks, without unit (or expressed as "pieces"). The number of breaks directly reflects the degree of continuity of the contour. The more breaks there are, the worse the continuity of the contour.

[0028] Get the preset maximum fracture length of fossil outlines from the database, in pixels, and the maximum fracture number of fossil outlines, without units (or expressed as "pieces").

[0029] Use edge detection algorithms (such as Canny edge detection) to extract the outline of the fossil, extract a series of discrete outline points from the outline, and for each outline point, calculate its curvature, which describes the degree of curvature of the outline at that point. Curvature can be calculated by a variety of methods, such as using a curvature estimation algorithm for a discrete point set, or by fitting a local curve (such as a circle or a parabola) to estimate the curvature. Calculate the average of the curvature values ​​of all outline points, calculate the square of the difference between each curvature value and the average, and find the average of these square differences (i.e., variance), and square the variance to get the standard deviation, i.e., the standard deviation of the fossil outline curvature, which has no unit. The curvature standard deviation reflects the degree of discreteness of the curvature change on the outline. The larger the standard deviation, the more drastic the curvature change and the worse the consistency, indicating that the curvature of the outline changes drastically, and there may be fragmentation, deformation, or other factors.

[0030] Get the preset maximum curvature standard deviation of the fossil outline from the database, without unit.

[0031] By analyzing the integrity of the fossil area from the aspects of the intersection area of ​​fossil areas, the union area of ​​fossil areas, the area of ​​fossil areas, the minimum complete fossil area, the length of fossil outline breaks, the maximum length of fossil outline breaks, the number of fossil outline breaks, the maximum number of fossil outline breaks, the standard deviation of fossil outline curvature, and the standard deviation of the maximum curvature of fossil outline, the analysis of the integrity of the fossil area is more comprehensive, which is conducive to more accurately defining the integrity of the fossil area.

[0032] When the fossil area integrity evaluation value is less than the preset fossil area integrity threshold obtained from the database, it indicates that the fossil area integrity is unqualified, and feature extraction is not performed on the fossil retrieval image. Instead, the user is prompted to re-enter the fossil retrieval image. When the fossil area integrity of the monitored fossil retrieval image is qualified, feature extraction is performed on the fossil retrieval image; in other cases, it indicates that the fossil area integrity is qualified, and feature extraction is performed on the fossil retrieval image.

[0033] Furthermore, to quantify the integrity degree of the area based on the fossil area integrity data, the specific process for obtaining the fossil area integrity evaluation value is as follows: Compare the intersection area of the fossil areas with the union area of the fossil areas, and obtain the overlap index by weighting the result of the comparison process with the intersection area weight factor; Compare the fossil area with the minimum complete fossil area, and obtain the area index by weighting the result of the comparison process with the area weight factor; Compare the fossil contour fracture length with the maximum fracture length of the fossil contour, and obtain the fracture length score by weighting the result of the comparison process with the fracture length weight factor; After comparing the number of fossil contour fractures with the maximum number of fossil contour fractures, obtain the fracture number score by weighting the result of the comparison operation with the fracture number weight factor; Couple the fracture length score and the fracture number score and then perform an inverse ratio operation, and obtain the contour fracture degree index by weighting the result of the inverse ratio operation with the contour fracture degree weight factor; Compare the standard deviation of the maximum curvature of the fossil contour with the standard deviation of the curvature of the fossil contour, and obtain the curvature index by weighting the result of the comparison operation with the contour curvature weight factor; Combine the overlap index, area index, contour fracture degree index, and curvature index through coupling processing to obtain the fossil area integrity evaluation value.

[0034] In this embodiment, the specific method for obtaining the fossil area integrity evaluation value is:

[0035]

[0036] Where ρ represents the evaluation value of the integrity of the fossil area in the fossil area, QQR represents the intersection area of the fossil area and the standardized complete fossil template, QQT represents the union area of the fossil area and the standardized complete fossil template, QQW represents the area of the fossil area, QW represents the area of the smallest complete fossil, QQU represents the fracture length of the fossil contour, QU represents the maximum fracture length of the fossil contour, QQL represents the number of fractures of the fossil contour, QL represents the maximum number of fractures of the fossil contour, QQJ represents the standard deviation of the curvature of the fossil contour, QJ represents the maximum standard deviation of the curvature of the fossil contour, ρ1 represents the intersection area weight factor, ρ2 represents the area weight factor, ρ3 represents the contour fracture degree weight factor, ρ4 represents the contour curvature weight factor, Q1 represents the fracture length weight factor, and Q1 represents the fracture number weight factor.

[0037] When the ratio of the intersection area of the fossil area to the union area of the fossil area is smaller, it indicates that the probability of damage and incompleteness of the fossil retrieval image is greater, and the area of the fossil area may be smaller. The smaller the ratio of the area of the fossil area to the area of the smallest complete fossil, the more serious the damage to the fossil area of the fossil retrieval image. Therefore, when the fracture length of the fossil contour is larger and the ratio to the maximum fracture length of the fossil contour is larger, and the number of fractures of the fossil contour is larger and the ratio to the maximum number of fractures of the fossil contour is larger, the corresponding standard deviation of the curvature of the fossil contour is larger, and the ratio of the maximum standard deviation of the curvature of the fossil contour to the standard deviation of the curvature of the fossil contour is smaller. Therefore, the smaller the evaluation value of the integrity of the fossil area, the smaller the integrity of the fossil area of the fossil retrieval image.

[0038] Obtain the intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor from the database. The intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor respectively represent the influence degrees of the overlap index, area index, contour fracture degree index, and curvature index on the evaluation value of the integrity of the fossil area. And there is a one-to-one mapping relationship between the overlap index, area index, contour fracture degree index, and curvature index and the corresponding intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor, and it satisfies that the sum of the intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor is equal to one. For example, input the real-time overlap index, area index, contour fracture degree index, and curvature index into the corresponding mapping relationship to obtain the corresponding intersection area weight factor, area weight factor, contour fracture degree weight factor, and contour curvature weight factor.

[0039] Obtain the fracture length weight factor and the fracture number weight factor from the database. The fracture length weight factor and the fracture number weight factor respectively represent the influence degrees of the fossil contour fracture length and the fossil contour fracture number on the evaluation value of the fossil area integrity. Moreover, there is a one-to-one mapping relationship between the fossil contour fracture length and the corresponding fracture length weight factor, and between the fossil contour fracture number and the corresponding fracture number weight factor, and it satisfies that the sum of the fracture length weight factor and the fracture number weight factor is equal to one. For example, input the real-time fossil contour fracture length and the fossil contour fracture number into the corresponding mapping relationship to obtain the corresponding fracture length weight factor and fracture number weight factor.

[0040] Further, the specific analysis process for analyzing whether to perform fossil retrieval image processing adjustment after fossil retrieval image feature extraction is as follows: After fossil retrieval image feature extraction, obtain the fossil area feature extraction effect data; the fossil area feature extraction effect data includes: the Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, and the contrast of the fossil area; quantify the fossil area feature extraction effect according to the fossil area feature extraction effect data to obtain the fossil area feature extraction effect evaluation value, and the fossil area feature extraction effect evaluation value is used to quantitatively analyze the feature extraction effect of the fossil area of the fossil retrieval image; judge whether to perform fossil retrieval image processing adjustment according to the fossil area feature extraction effect evaluation value.

[0041] In this embodiment, the proportion of low-frequency components in the blurred image is too high, and the detailed shape information will be lost. The Fourier descriptor feature descriptor may not accurately reflect the shape characteristics of the fossil in the blurred image. In the analysis of fossil retrieval images, this detailed shape information is of great significance for identifying the species, age, etc. of the fossil. The blurred image may cause the values of these feature descriptors to deviate from the true values, thus affecting the subsequent classification and recognition results.

[0042] Noise interference will cause abnormalities in the GLCM (Gray-level Co-occurrence Matrix) texture metrics (such as contrast, entropy value). When the signal-to-noise ratio (SNR) is lower, the errors of these metrics will increase significantly. In fossil retrieval images, noise may mask or distort the texture information of the fossil, making the GLCM texture metrics unable to accurately reflect the texture characteristics of the fossil. This will affect the analysis of aspects such as the surface structure and sedimentary environment of the fossil.

[0043] As a quantization index of sharpness, the higher the value of the Laplacian variance, the clearer the image. In the extraction of fossil retrieval image features, a higher Laplacian variance usually means more accurate contour parameters and richer shape information.

[0044] As a quantization index of the noise level, the higher the signal-to-noise ratio and the lower the noise variance, the better the image quality. In the feature extraction of fossil retrieval images, a higher signal-to-noise ratio and a lower noise variance generally mean more accurate texture indexes and more reliable microstructure information.

[0045] Therefore, analyzing the feature extraction effect of fossil retrieval images from the Laplacian variance of the fossil area, the preset Laplacian variance of the fossil area, the noise level of the fossil area, the preset noise level of the fossil area, the proportion of high-frequency components in the fossil area, the preset proportion of high-frequency components in the fossil area, the contrast of the fossil area, the preset contrast of the fossil area, the entropy value of the fossil area, and the preset entropy value of the fossil area can more accurately clarify the feature extraction effect.

[0046] Further, the specific process of judging whether to adjust the fossil retrieval image processing according to the evaluation value of the fossil area feature extraction effect is as follows: obtain the preset feature extraction effect threshold from the database. When the evaluation value of the fossil area feature extraction effect is less than the preset feature extraction effect threshold obtained from the database, perform fossil retrieval image processing adjustment; in other cases, do not perform fossil retrieval image processing adjustment.

[0047] In this embodiment, when the evaluation value of the fossil area feature extraction effect is less than the preset feature extraction effect threshold obtained from the database, it indicates that the feature extraction effect of the fossil area is unqualified, and fossil retrieval image processing adjustment is performed; in other cases, it indicates that the feature extraction effect of the fossil area is qualified, and fossil retrieval image processing adjustment is not performed.

[0048] Further, the fossil retrieval image processing adjustment includes Laplacian sharpening adjustment, high-pass filtering adjustment and warning prompt; the specific process of Laplacian sharpening adjustment is as follows: map the evaluation value of the fossil area feature extraction effect to obtain the corresponding Laplacian kernel value, convolve the fossil retrieval image with the Laplacian operator of the Laplacian kernel value to obtain the sharpened fossil retrieval image, and analyze whether the evaluation value of the fossil area feature extraction effect of the fossil retrieval image is not less than the preset feature extraction effect threshold obtained from the database. When the evaluation value of the fossil area feature extraction effect of the fossil retrieval image is less than the preset feature extraction effect threshold obtained from the database, repeat the above adjustment. When the growth range of the Laplacian variance is less than the preset Laplacian variance growth range or the evaluation value of the fossil area feature extraction effect is not less than the preset feature extraction effect threshold obtained from the database, stop the Laplacian sharpening adjustment; the specific process of high-pass filtering adjustment is as follows: when the evaluation value of the fossil area feature extraction effect is less than the preset feature extraction effect threshold obtained from the database when the Laplacian sharpening adjustment is stopped, obtain the corresponding filtering intensity according to the evaluation value of the fossil area feature extraction effect, perform high-pass filtering on the fossil retrieval image with the filtering intensity, and analyze whether the evaluation value of the fossil area feature extraction effect of the fossil retrieval image after high-pass filtering is not less than the preset feature extraction effect threshold obtained from the database. When the evaluation value of the fossil area feature extraction effect of the fossil retrieval image is less than the preset feature extraction effect threshold obtained from the database, repeat the above adjustment. When the proportion of the high-frequency components of the fossil retrieval image is greater than the preset proportion of the high-frequency components or the evaluation value of the fossil area feature extraction effect is not less than the preset feature extraction effect threshold obtained from the database, stop the high-pass filtering adjustment; the specific process of the warning prompt is as follows: when the evaluation value of the fossil area feature extraction effect is less than the preset feature extraction effect threshold obtained from the database when the high-pass filtering adjustment is stopped, it means that the effect of feature extraction after the fossil retrieval image is adjusted by Laplacian sharpening and high-pass filtering is unqualified, and the user is prompted to replace the fossil retrieval image.

[0049] In this embodiment, the Laplacian sharpening algorithm is used to enhance the edge and detail information in the image and improve the clarity of the image. The sharpening filter can emphasize the difference of edge pixels, making the details more distinct.

[0050] Using a high-pass filter allows high-frequency components to pass through while blocking low-frequency components. This can enhance the detail and texture information in the image and increase the proportion of high-frequency components.

[0051] Monitor the change of the Laplacian variance to evaluate the improvement of the image clarity. When the Laplacian variance increases to a certain extent and no longer increases significantly, it can be considered that the image clarity has been improved sufficiently.

[0052] Calculate the proportion of high-frequency components in the image by methods such as Fourier transform to evaluate the retention of image detail information. When the proportion of high-frequency components increases to a certain extent and the image details become richer, it can be considered that the high-frequency components are retained appropriately.

[0053] When the effect of feature extraction after Laplacian sharpening adjustment and high-pass filtering is unqualified, it means that the input fossil retrieval image is too blurred, and the user is prompted to re-enter a clearer fossil retrieval image.

[0054] Obtain the corresponding Laplacian kernel value and filtering intensity from the database according to the evaluation value of the fossil area feature extraction effect. There is a one-to-one or many-to-one mapping relationship between the evaluation value of the fossil area feature extraction effect and the Laplacian kernel value and filtering intensity. For example, obtain the corresponding Laplacian kernel value and filtering intensity according to the mapping relationship between the real-time evaluation value of the fossil area feature extraction effect and the Laplacian kernel value and filtering intensity.

[0055] Furthermore, the specific process of quantifying the fossil area feature extraction effect according to the fossil area feature extraction effect data to obtain the evaluation value of the fossil area feature extraction effect is as follows: Measure the variance deviation between the Laplacian variance of the fossil area and the preset Laplacian variance of the fossil area, and obtain the variance index by weighting the result of the variance deviation measurement with the variance weight factor; Couple the noise level of the fossil area with the preset noise level of the fossil area and then compare it with the preset noise level of the fossil area, and obtain the noise level index by weighting the result of the comparison process with the noise level weight factor; Measure the high-frequency component deviation between the proportion of high-frequency components in the fossil area and the preset proportion of high-frequency components in the fossil area and then compare it with the preset proportion of high-frequency components in the fossil area, and obtain the high-frequency component proportion index by weighting the result of the comparison process with the high-frequency component weight factor; Compare the contrast of the fossil area with the preset contrast of the fossil area, and obtain the contrast index by weighting the result of the comparison process with the contrast weight factor; Compare the preset entropy value of the fossil area with the entropy value of the fossil area, and obtain the entropy value index by weighting the result of the comparison process with the entropy value weight factor; Combine the variance index, noise level index, high-frequency component proportion index, contrast index and entropy value index for coupling processing to obtain the evaluation value of the fossil area feature extraction effect.

[0056] In this embodiment, the method for obtaining the Laplacian variance of the fossil area: Use the Laplacian operator to perform a convolution operation on the image of the fossil area, calculate the Laplacian value of each pixel point, and calculate the variance of the Laplacian values of all pixel points to obtain the Laplacian variance of the fossil area, which has no unit. Specifically, when implementing, the Laplacian function and variance calculation function in an image processing library (such as OpenCV) can be used.

[0057] Method for obtaining the noise level of the fossil area: The noise level can be evaluated by calculating the signal-to-noise ratio (SNR) of the image. The signal-to-noise ratio can be obtained by calculating the ratio of the image signal power to the noise power. Unit: The signal-to-noise ratio (SNR) is usually in decibels (dB).

[0058] Method for obtaining the proportion of high-frequency components in the fossil area: Use Fourier transform to convert the fossil area image into the frequency domain. Calculate the energy or amplitude of the high-frequency components in the frequency domain and compare it with the total energy or amplitude to obtain the proportion of high-frequency components, which has no unit. In specific implementation, the Fourier transform function and energy calculation function in the image processing library can be used.

[0059] Method for obtaining the contrast of the fossil area: Calculate the standard deviation of the gray histogram in the fossil area image, which has no unit.

[0060] Method for obtaining the entropy value of the fossil area: Calculate the entropy value of the gray histogram of the fossil area image according to the information entropy calculation formula. Unit: bit, which reflects the complexity and information content of the gray distribution in the image.

[0061] Obtain the preset Laplacian variance of the fossil area, which has no unit, the preset noise level of the fossil area, unit: the signal-to-noise ratio (SNR) is usually in decibels (dB), the preset proportion of high-frequency components in the fossil area, which has no unit, the preset contrast of the fossil area, which has no unit, and the preset entropy value of the fossil area, unit: bit, from the database.

[0062] The specific method for obtaining the evaluation value of the fossil area feature extraction effect is as follows:

[0063]

[0064] In the formula, represents the evaluation value of the fossil area feature extraction effect, LLO represents the Laplacian variance of the fossil area, LO represents the preset Laplacian variance of the fossil area, LLZ represents the noise level of the fossil area, LZ represents the preset noise level of the fossil area, LLR represents the proportion of high-frequency components in the fossil area, LR represents the preset proportion of high-frequency components in the fossil area, LLK represents the contrast of the fossil area, LK represents the preset contrast of the fossil area, LLU represents the entropy value of the fossil area, LU represents the preset entropy value of the fossil area, represents the variance weight factor, represents the noise level weight factor, represents the high-frequency component weight factor, represents the contrast weight factor, represents the entropy value weight factor.

[0065] Obtain the variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor, and entropy value weight factor from the database. The variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor, and entropy value weight factor respectively represent the influence degrees of the Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, the contrast of the fossil area, and the entropy value of the fossil area on the evaluation value of the fossil area feature extraction effect. Moreover, there is a one-to-one mapping relationship between the Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, the contrast of the fossil area, and the entropy value of the fossil area and the corresponding variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor, and entropy value weight factor, and it satisfies that the sum of the variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor, and entropy value weight factor is equal to one. For example, input the real-time Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, the contrast of the fossil area, and the entropy value of the fossil area into the corresponding mapping relationship to obtain the corresponding variance weight factor, noise level weight factor, high-frequency component weight factor, contrast weight factor, and entropy value weight factor.

[0066] Furthermore, the specific analysis process for analyzing and judging whether to output the retrieval information for the retrieval information is as follows: Obtain the retrieval result matching data according to the retrieval information and the retrieval text, and analyze the retrieval result matching degree based on the retrieval result matching data. The retrieval result matching degree is used to quantitatively analyze the content matching degree between the retrieval information and the retrieval text; analyze the content matching degree of the retrieval information according to the retrieval result matching degree; the specific analysis process for analyzing the content matching degree of the retrieval information according to the retrieval result matching degree is as follows: Obtain the preset first threshold for retrieval result matching and the second threshold for retrieval result matching from the database. When the retrieval result matching degree is less than the preset first threshold for retrieval result matching obtained from the database, it indicates that the retrieval information is completely matched; when the retrieval result matching degree is not less than the preset first threshold for retrieval result matching obtained from the database and not greater than the second threshold for retrieval result matching, it indicates that the retrieval information is incompletely matched; when the retrieval result matching degree is greater than the preset first threshold for retrieval result matching obtained from the database, it indicates that the retrieval information is not matched; perform retrieval output feedback according to the content matching degree of the retrieval information.

[0067] In this embodiment, the smaller the retrieval result matching degree is, the lower the content matching degree of the retrieval information is; the larger the retrieval result matching degree is, the higher the content matching degree of the retrieval information is.

[0068] Further, the specific analysis process for retrieving output feedback based on the content matching degree of the retrieved information is as follows: when the retrieved information is completely matched, the corresponding retrieved information is output as the retrieval result; when the retrieved information is not completely matched, it is prompted that the retrieved information is not completely matched, and a selection operation of whether to output the retrieved information as the retrieval result is sent to the user. When the user selects "yes", the retrieved information is output as the retrieval result; otherwise, the user is prompted to supplement the retrieval text until the corresponding retrieved information is output as the retrieval result; when the retrieved information does not match, the user is prompted to supplement the retrieval text until the corresponding retrieved information is output as the retrieval result.

[0069] In this embodiment, when the retrieved information is completely matched, the probability that the retrieved information is the content expected by the user is high, and the corresponding retrieved information is output as the retrieval result; when the retrieved information is not completely matched, the probability that the retrieved information is the content expected by the user is medium, and it is prompted that the retrieved information is not completely matched, and a selection operation of whether to output the retrieved information as the retrieval result is sent to the user. When the user selects "yes", the retrieved information is output as the retrieval result; otherwise, the user is prompted to supplement the retrieval text until the corresponding retrieved information is output as the retrieval result; when the retrieved information does not match, the probability that the retrieved information is the content expected by the user is low, and the user is prompted to supplement the retrieval text until the corresponding retrieved information is output as the retrieval result

[0070] Further, the retrieved result matching data includes: the retrieved topic matching degree score, the core content coverage, the detail information consistency rate, and the semantic similarity score; the specific analysis process for obtaining the retrieved result matching degree based on the retrieved result matching data analysis is as follows: the retrieved topic matching degree score is weighted with the retrieved topic matching degree score weight factor to obtain the retrieved topic index; the core content coverage is weighted with the core content coverage weight factor to obtain the core content index; the detail information consistency rate is weighted with the detail information consistency rate weight factor to obtain the information detail index; the semantic similarity score is weighted with the semantic similarity score weight factor to obtain the semantic similarity index; the retrieved result matching degree is obtained by coupling the retrieved topic index, the core content index, the information detail index, and the semantic similarity index.

[0071] In this embodiment, a text classification algorithm (such as TF-IDF combined with a Naive Bayes classifier) is used to classify the retrieved text and the text corresponding to the retrieved information to determine whether they belong to the same topic category, and the topic matching degree score (ranging from 0 to 1, where 1 represents complete match) is obtained, without unit.

[0072] The computer extracts the key information points (such as species name, geological age, morphological features, etc.) in the retrieved text, and checks whether these information points are included in the text corresponding to the retrieved information to obtain the core content coverage (the number of covered information points / the total number of information points), without unit.

[0073] The computer compares the specific detailed information (such as size, color, storage status, etc.) in the retrieved text and the text corresponding to the retrieved information one by one to obtain the consistency rate of detailed information (the number of consistent detailed information / the total number of detailed information), without unit.

[0074] Use a word vector model (such as Word2Vec, GloVe, etc.) to convert the retrieved text and the text corresponding to the retrieved information into vector representations, calculate the cosine similarity between the two vectors as the semantic similarity score, and obtain the semantic similarity score (between 0 and 1, where 1 represents complete similarity), without unit.

[0075] The specific method for obtaining the retrieval result matching degree is as follows:

[0076] γ = KKX * γ1 + KKF * γ2 + KKS * γ3 + KKA * γ4;

[0077] In the formula, γ represents the retrieval result matching degree, KKX represents the retrieval topic matching degree score, KKF represents the core content coverage, KKS represents the consistency rate of detailed information, KKA represents the semantic similarity score, γ1 represents the weight factor of the retrieval topic matching degree score, γ2 represents the weight factor of the core content coverage, γ3 represents the weight factor of the consistency rate of detailed information, and γ4 represents the weight factor of the semantic similarity score.

[0078] Obtain the weight factors of the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score from the database. The weight factors of the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score respectively represent the influence degrees of the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score on the evaluation value of the fossil area feature extraction effect. And there is a one-to-one mapping relationship between the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, the semantic similarity score and the corresponding weight factors of the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score, and it satisfies that the sum of the weight factors of the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score is equal to one. For example, input the real-time retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score into the corresponding mapping relationship to obtain the corresponding weight factors of the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score.

[0079] By analyzing the content matching degree between the retrieved information and the retrieved text from four aspects: the retrieval topic matching degree score, the core content coverage, the consistency rate of detailed information, and the semantic similarity score, the accuracy of analyzing the content matching degree between the retrieved information and the retrieved text is higher, which is beneficial to outputting more accurate retrieval results.

[0080] For the technical solutions in the embodiments of the present application above, by inputting the fossil retrieval image and the retrieved text into the standard database of paleontological fossils, analyzing the integrity of the fossil area according to the fossil retrieval image and determining whether to extract the features of the fossil retrieval image, after extracting the features of the fossil retrieval image, analyzing whether to adjust the processing of the fossil retrieval image, and after adjusting the processing of the fossil retrieval image, retrieving to obtain the retrieved information according to the obtained features of the fossil retrieval image and the retrieved text, and analyzing and determining whether to output the retrieved information, so as to output the retrieved information with high content accuracy as the retrieval result, thereby improving the retrieval effectiveness of the standard database of paleontological fossils and effectively solving the problem that the retrieval results provided by the standard database of paleontological fossils in the prior art are inaccurate.

[0081] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0082] The present invention is described with reference to the flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0083] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means realizes the functions in the process Figure 1 one process or multiple processes and / or blocksFigure 1 The functions specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 process or more processes and / or boxes Figure 1 or more boxes.

[0085] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be construed as including the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0086] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A special service system for the standard database of paleontological fossils, characterized in that, It includes: An information input module, a feature extraction module, an image processing module, and a retrieval output module; Among them, the information input module: is used to input the fossil retrieval image and the retrieval text into the paleontological fossil standard database; The feature extraction module: is used to analyze the integrity of the fossil area based on the fossil retrieval image and determine whether to extract the features of the fossil retrieval image; The image processing module: is used to analyze whether to adjust the fossil retrieval image processing after extracting the features of the fossil retrieval image; The retrieval output module: is used to retrieve the retrieval information based on the obtained fossil retrieval image features and the retrieval text after the fossil retrieval image processing is adjusted, and analyze whether to output the retrieval information for the retrieval information.

2. The paleontological fossil standard database special service system according to claim 1, wherein The specific analysis process of analyzing the integrity of the fossil area based on the fossil retrieval image is as follows: Obtain the fossil area integrity data according to the fossil retrieval image; The fossil area integrity data includes: the intersection area of the fossil area, the union area of the fossil area, the area of the fossil area, the fracture length of the fossil contour, the number of fractures of the fossil contour, and the standard deviation of the curvature of the fossil contour; Quantify the integrity degree of the area according to the fossil area integrity data to obtain the fossil area integrity evaluation value, and the fossil area integrity evaluation value is used to quantitatively analyze the integrity of the fossil area in the fossil retrieval image; Compare the fossil area integrity evaluation value with the preset fossil area integrity threshold obtained from the database. When the fossil area integrity evaluation value is less than the preset fossil area integrity threshold obtained from the database, it indicates that the fossil area integrity is unqualified; In other cases, it indicates that the fossil area integrity is qualified; The specific analysis process of determining whether to extract the features of the fossil retrieval image is as follows: When the fossil area integrity is qualified, extract the features of the fossil retrieval image; When the fossil area integrity is unqualified, do not extract the features of the fossil retrieval image, prompt the user to re-enter the fossil retrieval image, and when the fossil area integrity of the monitored fossil retrieval image is qualified, extract the features of the fossil retrieval image.

3. The special service system of the standard database for paleontological fossils according to claim 2, characterized in that, The specific process of quantifying the integrity degree of the area according to the fossil area integrity data to obtain the fossil area integrity evaluation value is as follows: Compare the intersection area of the fossil area with the union area of the fossil area, and obtain the overlap index by weighting the result of the comparison process through the intersection area weight factor; Compare the area of the fossil area with the minimum complete fossil area, and obtain the area index by weighting the result of the comparison process through the area weight factor; Compare the fracture length of the fossil contour with the maximum fracture length of the fossil contour, and obtain the fracture length score by weighting the result of the comparison process through the fracture length weight factor; After comparing the number of fractures of the fossil contour with the maximum number of fractures of the fossil contour, obtain the fracture number score by weighting the result of the comparison operation through the fracture number weight factor; Couple the fracture length score and the fracture number score and then perform an inverse ratio operation, and obtain the contour fracture degree index by weighting the result of the inverse ratio operation through the contour fracture degree weight factor; Compare the standard deviation of the maximum curvature of the fossil contour with the standard deviation of the curvature of the fossil contour, and obtain the curvature index by weighting the result of the comparison operation through the contour curvature weight factor; Combine the overlap index, area index, contour fracture degree index, and curvature index for coupling processing to obtain the fossil area integrity evaluation value.

4. The special service system of the standard database of paleontological fossils according to claim 1, characterized in that, The specific analysis process for analyzing whether to adjust the fossil retrieval image processing after extracting the features of the fossil retrieval image is as follows: After extracting the features of the fossil retrieval image, obtain the data on the feature extraction effect of the fossil area; The data on the feature extraction effect of the fossil area includes: the Laplacian variance of the fossil area, the noise level of the fossil area, the proportion of high-frequency components in the fossil area, and the contrast of the fossil area; Quantify the feature extraction effect of the fossil area according to the data on the feature extraction effect of the fossil area, and obtain the evaluation value of the feature extraction effect of the fossil area. The evaluation value of the feature extraction effect of the fossil area is used to quantitatively analyze the feature extraction effect of the fossil area in the fossil retrieval image; Judge whether to adjust the fossil retrieval image processing according to the evaluation value of the feature extraction effect of the fossil area.

5. The special service system of the standard database of paleontological fossils according to claim 4, characterized in that, The specific process for judging whether to adjust the fossil retrieval image processing according to the evaluation value of the feature extraction effect of the fossil area is as follows: Obtain the preset feature extraction effect threshold from the database. When the evaluation value of the feature extraction effect of the fossil area is less than the preset feature extraction effect threshold obtained from the database, perform the adjustment of the fossil retrieval image processing; In other cases, do not perform the adjustment of the fossil retrieval image processing.

6. The specialized service system of the paleontological fossil standard database according to claim 4, characterized in that, The adjustment of the fossil retrieval image processing includes Laplacian sharpening adjustment, high-pass filtering adjustment, and warning prompt; The specific process of the Laplacian sharpening adjustment is as follows: Map to the corresponding Laplacian kernel value with the evaluation value of the feature extraction effect of the fossil area, and perform convolution on the fossil retrieval image with the Laplacian operator of the Laplacian kernel value to obtain the sharpened fossil retrieval image. Analyze whether the evaluation value of the feature extraction effect of the fossil area of this fossil retrieval image is not less than the preset feature extraction effect threshold obtained from the database. When the evaluation value of the feature extraction effect of the fossil area of this fossil retrieval image is less than the preset feature extraction effect threshold obtained from the database, repeat the above adjustment. When the growth range of the Laplacian variance is less than the preset Laplacian variance growth range or the evaluation value of the feature extraction effect of the fossil area is not less than the preset feature extraction effect threshold obtained from the database, stop the Laplacian sharpening adjustment; The specific process of the high-pass filtering adjustment is as follows: When the evaluation value of the fossil area feature extraction effect is less than the preset feature extraction effect threshold obtained from the database when the Laplacian sharpening adjustment is stopped, the corresponding filtering intensity is obtained according to the evaluation value of the fossil area feature extraction effect, and the fossil retrieval image is subjected to high-pass filtering with this filtering intensity. When the evaluation value of the fossil area feature extraction effect of the fossil retrieval image after high-pass filtering is less than the preset feature extraction effect threshold obtained from the database, the above adjustment is repeated. When the proportion of high-frequency components of the fossil retrieval image is greater than the preset proportion of high-frequency components or the evaluation value of the fossil area feature extraction effect is not less than the preset feature extraction effect threshold obtained from the database, the high-pass filtering adjustment is stopped.

7. The special service system of the standard database for paleontological fossils according to claim 4, characterized in that, The specific process of quantifying the fossil area feature extraction effect based on the fossil area feature extraction effect data to obtain the evaluation value of the fossil area feature extraction effect is as follows: Measure the variance deviation between the Laplacian variance of the fossil area and the preset Laplacian variance of the fossil area, and obtain the variance index by weighting the result of the variance deviation measurement with the variance weight factor; Perform coupling processing on the noise level of the fossil area and the preset noise level of the fossil area, and then perform comparison processing with the preset noise level of the fossil area. Obtain the noise level index by weighting the result of the comparison processing with the noise level weight factor; Measure the high-frequency component deviation between the proportion of high-frequency components in the fossil area and the preset proportion of high-frequency components in the fossil area, and then perform comparison processing with the preset proportion of high-frequency components in the fossil area. Obtain the high-frequency component proportion index by weighting the result of the comparison processing with the high-frequency component weight factor; Perform comparison processing on the contrast of the fossil area and the preset contrast of the fossil area, and obtain the contrast index by weighting the result of the comparison processing with the contrast weight factor; Perform comparison processing on the preset entropy value of the fossil area and the entropy value of the fossil area, and obtain the entropy value index by weighting the result of the comparison processing with the entropy value weight factor; Perform coupling processing on the variance index, noise level index, high-frequency component proportion index, contrast index and entropy value index to obtain the evaluation value of the fossil area feature extraction effect.

8. The special service system for the standard database of paleontological fossils according to claim 1, characterized in that, The specific analysis process of analyzing and judging whether to output the retrieval information for the retrieval information is as follows: Obtain the retrieval result matching data according to the retrieval information and the retrieval text, Analyze the retrieval result matching degree based on the retrieval result matching data. The retrieval result matching degree is used to quantitatively analyze the content matching degree between the retrieval information and the retrieval text; Analyze the content matching degree of the retrieval information based on the retrieval result matching degree; The specific analysis process of analyzing the content matching degree of the retrieval information based on the retrieval result matching degree is as follows: Obtain the preset first retrieval result matching threshold and the second retrieval result matching threshold from the database. When the retrieval result matching degree is less than the preset first retrieval result matching threshold obtained from the database, it means that the retrieval information is completely matched; When the retrieval result matching degree is not less than the preset first retrieval result matching threshold obtained from the database and not greater than the second retrieval result matching threshold, it means that the retrieval information is incompletely matched; When the matching degree of the retrieval result is greater than the first preset retrieval result matching threshold obtained from the database, it indicates that the retrieval information does not match; Perform retrieval output feedback according to the content matching degree of the retrieval information.

9. The special service system for the standard database of paleontological fossils as described in claim 8, wherein, The specific analysis process of performing retrieval output feedback according to the content matching degree of the retrieval information is as follows: When the retrieval information is completely matched, output the corresponding retrieval information as the retrieval result; When the retrieval information is not completely matched, send a selection operation to the user on whether to output the retrieval information as the retrieval result. When the user selects "yes", output the retrieval information as the retrieval result; otherwise, prompt the user to supplement the retrieval text; When the retrieval information does not match, prompt the user to supplement the retrieval text until the corresponding retrieval information is output as the retrieval result.

10. The special service system of the standard database for paleontological fossils according to claim 8, characterized in that, The retrieval result matching data includes: retrieval topic matching degree score, core content coverage, detail information consistency rate, and semantic similarity score; The specific analysis process of obtaining the retrieval result matching degree based on the analysis of the retrieval result matching data is as follows: Perform weight assignment processing on the retrieval topic matching degree score and the retrieval topic matching degree score weight factor to obtain the retrieval topic index; Perform weight assignment processing on the core content coverage and the core content coverage weight factor to obtain the core content index; Perform weight assignment processing on the detail information consistency rate and the detail information consistency rate weight factor to obtain the information detail index; Perform weight assignment processing on the semantic similarity score and the semantic similarity score weight factor to obtain the semantic similarity index; Combine the retrieval topic index, core content index, information detail index, and semantic similarity index for coupling processing to obtain the retrieval result matching degree.

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