Unlock instant, AI-driven research and patent intelligence for your innovation.

Optimization method and system for stone carving character recognition

A technology of text recognition and optimization method, which is applied in the field of optimization method and system of stone inscription text recognition, which can solve the problems of high recognition ability and fuzzy scenes that cannot be realized, and achieve the effect of improving accuracy and service ability of scenic spots

Pending Publication Date: 2021-12-14
ZHEJIANG LISHI TECH
View PDF1 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention discloses an optimization method and system for stone inscription text recognition, which is used to solve the problems of the existing text recognition technology in scenic spot scenes, scenes with poor weather and light at night, rainy days, etc., and stone inscription paint The problem that blurred scenes after weathering cannot achieve high recognition ability

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Optimization method and system for stone carving character recognition
  • Optimization method and system for stone carving character recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0026] This embodiment discloses as figure 1 An optimization method for recognition of stone inscriptions is shown, comprising the following steps:

[0027] S1 obtains pictures of stone carvings in special environments, and uses convolutional neural networks to train models of stone carvings in special environments;

[0028] After N iterations of S2, the parameters trained in the special environment stone carving model are superimposed on the daily stone carving training process of each layer, and used as the offset value after each layer of convolution to enter the next layer of convolution, where N is a natural number;

[0029] S3 extracts features in the convolutional layer, uses feature value deconvolution to restore the original picture, and restores the features of the original picture;

[0030] S4 performs convolution processing on the restored image, obtains the features of the generated image, and then confronts the original image, and finally obtains an optimized mo...

Embodiment 2

[0036] This embodiment provides an optimization method for stone inscription recognition, referring to figure 2 As shown, in this embodiment, the convolutional neural network is used to train pictures of stone carvings in a special environment, and the results corresponding to each picture are used as labels for training the model. Special environment stones are first trained individually for N iterations, where N is an integer. The model will first obtain a part of the stone inscription content features, and remove irrelevant features.

[0037] Then, the parameters after the training of the special environment stone carving model are superimposed on the daily stone carving training process of each layer, as the offset value after each layer of convolution, and enter the next layer of convolution. After the features are extracted by the convolutional layer, the original image is restored by using the feature value deconvolution, and the loss function is used to continuously ...

Embodiment 3

[0041] This embodiment provides a specific application of an optimization method for stone inscription text recognition, training sample data, selecting different fonts in a daily sunny environment, 10 different scenic spots, and 50 photos from different angles for each scenic spot, a total of 500 photos. Select the same 10 scenic spots for special environment training pictures. In rainy days, cloudy days and other links, 50 pictures are taken from the same angle, and a total of 500 pictures are used for training.

[0042] Convolution parameters:

[0043] Input image size: 2560x1920 pixels

[0044] Convolution 1, Convolution 2: 5 convolutional layers, filter size 10x10, using maximum pooling, offset: 10 pixels

[0045] Convolution 3: 5 convolutional layers, filter size 15x15, max pooling, offset: 10 pixels

[0046] Deconvolution 1: 5 convolutional layers, filter size 10x10, offset: 10 pixels

[0047] Learning rate: 0.005, when the loss function value is lower than 0.01, the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of character recognition, in particular to an optimization method and system for stone carving character recognition. The method comprises the following steps: obtaining a special environment stone carving picture, and training a special environment stone carving model through a convolutional neural network; after N iterations are carried out, superposing parameters after training of the special environment stone carving model to a daily stone carving training process of each layer to serve as deviation values after each layer of convolution, and entering the next layer of convolution, wherein N is a natural number; extracting features in a convolutional layer, recovering an original picture by using feature value deconvolution, and restoring the features of the original picture; and carrying out convolution processing on the restored picture to obtain features of a generated picture, confronting the generated picture with the original picture, and finally obtaining a stone carving character recognition optimization model. According to the method provided by the invention, stone carving content can be recognized in an abnormal environment, different weather conditions and light conditions, the accuracy of stone carving content recognition is improved, and the scenic spot service capability is improved.

Description

technical field [0001] The invention relates to the technical field of character recognition, in particular to an optimization method and system for stone inscription character recognition. Background technique [0002] At present, the content recognition of stone carvings in scenic spots mainly uses the text recognition function designed and developed by neural networks such as convolutional neural networks, which has a good and high recognition rate for most scenes. The current text recognition function mainly focuses on the text recognition of book texts. There will be obvious deficiencies in the changing environment and objects of the scenic spot. For example, under different conditions such as different light conditions and different fonts, the existing text recognition function may be different does not have the desired effect. [0003] In the patent document whose patent application number is CN202110375519.8, a seal character recognition method, device, computer equ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/20G06K9/34G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/214Y02T10/40
Inventor 杨逸舟陈海江
Owner ZHEJIANG LISHI TECH