Abstract

The international tourism growth forces governments to make a big effort to improve the security of national borders. The compulsory passport stamping is used in guaranteeing the safekeeping of the entry point of the border. For each passenger, the border police must check the existence of exit stamps and/or the entry stamps of the country that the passenger visits, in all the pages of his passport. However, the systematic control considerably slows the operations of the border police. Protecting the borders from illegal immigrants and simplifying border checkpoints for law-abiding citizens and visitors is a delicate compromise. The purpose of this paper is to perform a flexible and scalable system that ensures faster, safer and more efficient stamp controlling. An automatic system of stamp extraction for travel documents is proposed. We incorporate several methods from the field of artificial intelligence, image processing and pattern recognition. At first, texture feature extraction is performed in order to find potential stamps. Next, image segmentation aimed at detecting objects of specific textures are employed. Then, isolated objects are extracted and classified using multi-layer perceptron artificial network. Promising results are obtained in terms of accuracy, with a maximum average of 0.945 among all the images, improving the performance of MLP neural network in all cases.

Highlights

  • International tourism is always on the rise; 1.5 billion tourist arrivals were recorded in 2019, globally

  • In order to effectively guarantee the safekeeping of the entry point, the European Union for example has introduced compulsory stamping of travel documents of third-country nationals when crossing the borders

  • Neural network training parameters after seveEradletfeinstest.hEe pdeerffionremtahnecepfeurnfocrtmionanthceat is in this work function tthhaet Mis einanthSisquwaorerkd tEhreroMr e(ManSSEq)udaerfeinded by the EquaError (MStEio)nd(e1f8in)ed by the equation (18)

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Summary

Introduction

International tourism is always on the rise; 1.5 billion tourist arrivals were recorded in 2019, globally. In order to effectively guarantee the safekeeping of the entry point, the European Union for example has introduced compulsory stamping of travel documents (passports) of third-country nationals when crossing the borders. The border police ensure that the passenger passport is stamped when he enters and leaves the country. We will introduce a system that helps the border control officers by doing these stamps checking operations automatically. Crossing the border without stamping the passport can cause real problems when leaving the country. In this case, the passenger risks being considered as a clandestine immigrant, which may be worthwhile for him to be detained, to pay a large fine and to be expelled.

Related Works
Object Classification
Stamp Extraction Extraction
MLP Neural Network Architecture for Passport Stamps Classification
Experimental Study
Conclusion
Findings
Methods
Full Text
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