This paper focuses on the correlation methods applicable for the recognition system of speed limit traffic signs and correlation methods comparison. The correlation method is one possible manner of the ocr algorithm (...
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ISBN:
(纸本)9783642330179
This paper focuses on the correlation methods applicable for the recognition system of speed limit traffic signs and correlation methods comparison. The correlation method is one possible manner of the ocr algorithm (Optical Character Recognition) used to determine the degree of similarity between the input matrix and the defined pattern matrix. The presented correlation methods are verified using the proposed comparison algorithm, where the output data are evaluated by statistical methods of the exploratory statistic data analysis. The part of the recognition system for ocr algorithm proceeds is very time consuming and the limitation of microcontroller type depends on frequency instruction processing. High accuracy of the recognition system can be achieved by increasing the resolution of camera system, by segmentation methods of input image signal, correlation method type.
The main application task, solving which the project aims to, is to help people with visual impairments and teach the correct pronunciation of words to people learning a Ukrainian language as a foreign language. This ...
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The main application task, solving which the project aims to, is to help people with visual impairments and teach the correct pronunciation of words to people learning a Ukrainian language as a foreign language. This problem is solved by developing software that will recognise text in video mode. As a result, when you tap the screen, you will hear how the selected text sounds.
In this article we describe an automatic initialization-free method for building and managing book catalogs. At the heart of the system there is an image processing algorithm which can analyze the contents of an image...
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ISBN:
(纸本)9781479953370
In this article we describe an automatic initialization-free method for building and managing book catalogs. At the heart of the system there is an image processing algorithm which can analyze the contents of an image taken of a bookshelf, separate the book spines into subsequent images and use an ocr algorithm on it to find the title and author of the book. The title and author information is searched for in public book databases to find all the details of the given book which can then be stored. The article describes the methods used along with accuracy measurements for the different modules of our system.
Aiming at the problem of courier slip information extraction in a complex environment, a courier slip image enhancement and detection algorithm based on affine transformation is studied and proposed, which enhances th...
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ISBN:
(纸本)9798350322514
Aiming at the problem of courier slip information extraction in a complex environment, a courier slip image enhancement and detection algorithm based on affine transformation is studied and proposed, which enhances the courier bill image in a complex environment by gamma transformation and automatic color equalization algorithm, and quickly locates the courier slip subject based on the barcode position in combination with the actual situation Then the affine transformation is introduced to detect the courier slip. Simulation and comparison experiment is conducted using Python and OpenCV, the results of which show that the algorithm can effectively improve the traditional ocr algorithm when the picture has low brightness or high exposure, the courier bill has a small proportion in the picture and the direction is difficult to determine, and improve the positioning efficiency and recognition success rate of the courier slips. It can be combined with technologies such as robotic arms and AGV omnidirectional mobile chassis and is widely used in various sorting scenarios such as logistics transfer.
Optical character recognition (ocr) is widely used for text recognition in various areas. It digitizes enormous texts efficiently with relatively high accuracy. However, the accuracy is severely undermined when texts ...
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ISBN:
(数字)9781665403870
ISBN:
(纸本)9781665403870
Optical character recognition (ocr) is widely used for text recognition in various areas. It digitizes enormous texts efficiently with relatively high accuracy. However, the accuracy is severely undermined when texts are deformed, stained, or under dim light. The paper adds human decision to the recognition process of the deep learning algorithm and enhances the algorithm's robustness and accuracy. We developed a mobile phone system that utilized the mainstream ocr technology to get the top N candidates sorted by confidence level and then properly displayed the candidates to the original text picture screened by the mobile phone camera. The final result is selected by a human finger tap on the right candidate. We conducted a first user study to compare the efficiency and accuracy between manual recognition and the developed system under several classical complex conditions, including stained, blurred, and incomplete text. The experiment results indicated that the system significantly improved text recognition efficiency and is dramatically faster than the manual recognition system. To explore more insights into our system, we conducted another user study to examine the influence of familiarity and encoding length. The results indicate that familiarity significantly influences recognition efficiency and correctness, but increasing length will actually increase the time spent on recognition.
Road transport is currently one of the most important sectors affecting sustainable development and the improvement of the population’s standard of living. In some sub-Saharan African countries, including Burundi, th...
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Road transport is currently one of the most important sectors affecting sustainable development and the improvement of the population’s standard of living. In some sub-Saharan African countries, including Burundi, the transport structure is vulnerable, under attack, or even damaged or destroyed. This is prompting decision-makers to look for every possible way to enable dynamic management of the road system, as well as the collection of tax revenues attributable to this sector. To reach this stage, we postulate that the introduction of the Intelligent Transport System (ITS) into the road tax and fee collection process would make a significant contribution (road safety, zero cash on silk Safety Officers, payment of a fine, eradication of road corruption etc.) to the digitization of the various transport sectors. As far as the city of Bujumbura is concerned (our field of intervention), the applicability of the present System could thus meet the expectations of the decision-maker, certain drivers and, by the same token, contribute to the promotion of Digital Technology in Burundi.
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