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1

Robotic process automation of unstructured data with machine learning

Wróblewska A., Stanisławek T., Prus-Zajączkowski B., Garncarek Ł.

Annals of Computer Science and Information Systems

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2018

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Vol. 16

9--16

EN

In this paper we present our work in progress on building an artificial intelligence system dedicated to tasks regarding the processing of formal documents used in various kinds of business procedures. The main challenge is to build machine learning (ML) models to improve the quality and efficiency of business processes involving image processing, optical character recognition (OCR), text mining and information extraction. In the paper we introduce the research and application field, some common techniques used in this area and our preliminary results and conclusions.

2

Rozpoznawanie wzorców cyfrowych za pomocą robota edukacyjnego

Dimitrova-Grekow T., Grodzki D.

Pomiary Automatyka Kontrola

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2014

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R. 60, nr 5

284--287

PL

Artykuł przedstawia system rozpoznający liczby rzymskie przy użyciu edukacyjnego zestawu Mindstorms NXT. Algorytm OCR wybrany do rozpoznania znaków został oparty na klasyfikacji cech. Zaadaptowana wersja algorytmu Region of Interest ROI i klasyfikacja cech są głównymi atutami tej pracy. System został skutecznie przetestowany pod wieloma względami. Powstała konstrukcja umożliwiająca skanowanie kartki formatu A4, a obsługujący ją program umożliwia prawidłową interpretację zeskanowanych liczb rzymskich.

EN

Pattern recognition is always associated with powerful calculation [1, 2]. A specific branch in this area is Optical Character Recognition [3, 4, 5] where one of the most popular techniques is Feature Extraction, also known as Intelligent Character Recognition [6]. All ICR algorithms are topological [7, 8, 9]. This paper presents an implementation of Roman Number Recognition system realized on LEGO Mindstorms NXT educational robot. The main point is successful minimalistic realization of an on-board pattern recognition system. The NXT platform allows also an easy reconfiguration of the hardware and more building freedom without extra costs (Fig. 1.). An adapted version of the ROI algorithm is implemented [10]. Based on the extracted features (Fig. 2.) a classification of the roman digits is proposed (Fig. 3.). The final stage of the program includes segmentation, end result calculation and visualization of it on the robot screen. The conducted experimental tests proved a 100% efficiency for digit and number recognition having a process in optimal conditions and quite good stability for the optical noises (Fig. 4.) and color chances (Tab. 1). In spite of many drawbacks of the hardware, the implemented system seems very perspective and invokes many ideas toward pattern recognition technics.

3

Cross-task code reuse in genetic programming applied to visual learning

Jaśkowski W., Krawiec K., Wieloch B.

International Journal of Applied Mathematics and Computer Science

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2014

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Vol. 24, no. 1

183--197

EN

We propose a method that enables effective code reuse between evolutionary runs that solve a set of related visual learning tasks. We start with introducing a visual learning approach that uses genetic programming individuals to recognize objects. The process of recognition is generative, i.e., requires the learner to restore the shape of the processed object. This method is extended with a code reuse mechanism by introducing a crossbreeding operator that allows importing the genetic material from other evolutionary runs. In the experimental part, we compare the performance of the extended approach to the basic method on a real-world task of handwritten character recognition, and conclude that code reuse leads to better results in terms of fitness and recognition accuracy. Detailed analysis of the crossbred genetic material shows also that code reuse is most profitable when the recognized objects exhibit visual similarity.

4

Methodology for the evaluation of the algorithms for text segmentation based on errors type

Brodic D.

Przegląd Elektrotechniczny

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2012

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R. 88, nr 1b

259-263

EN

Text segmentation represents the key element in the optical character recognition process. Hence, testing procedure for text segmentation algorithms has significance importance. All previous works deal mainly with text database as a template. They are used for testing as well as for the evaluation of the text segmentation algorithm. However, because of inconsistencies in this process, some methodology for the experiments is required. In this manuscript, methodology for the evaluation of the algorithm for text segmentation based on errors type is proposed. It is established on the various multiline text samples linked with text segmentation. Final result is obtained by comparative analysis of cross linked data. At the end, its suitability for different type of scripts represents its main advantage.

PL

Segmentacja tekstu stanowi kluczowy element procesu optycznego rozpoznawania znaków. Wszystkie dotychczasowe prace dotyczą głównie bazy danych tekstu jako szablonu. Są one używane do testowania, jak i dla oceny algorytmu segmentacji tekstu. Jednak w taki, algorytmie występują nieścisłości. W pracy przedstawiono , metodologię oceny algorytmu segmentacji tekstu w oparciu o typ błędów. Badania przeprowadzono na różnych próbkach tekstu wielowierszowego. Końcowy wynik uzyskuje się poprzez analizę porównawczą danych.

5

Basic experiments set for the evaluation of the text line segmentation

Brodic D.

Przegląd Elektrotechniczny

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2010

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R. 86, nr 11a

353-357

EN

Text line segmentation represents the key point of the optical character recognition process. All previous works deal primarily with various text database as a reference for the evaluation of the text line segmentation. Due to inconsistencies in measurement and evaluation of text line segmentation algorithm quality, some basic set of test experiments is required. In this paper, basic set of exepriments for the evaluation of the algorithm’s text line segmentation is proposed. This test set consists of a few experiments primarily linked to text line segmentation. Although they are mutually independent, the obtained results are strongly cross linked. At the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages.

PL

Segmentacja linii tekstu jest ważnym elementem optycznego rozpoznawania znaków. Większość dotychczasowych metod opierało się na bazach danych tekstów. Na skutek niespójności w detekcji i ocenie linii tekstu wymagane jest przeprowadzenie pewnych podstawowych testów. W artykule zaproponowano kilka eksperymentów umożliwiających ocenę algorytmów segmentacji linii tekstu. Chociaż eksperymenty są wzajemnie niezależne otrzymane rezultaty są ze sobą powiązane. Są one możliwe do zastosowania dla różnych typów liter oraz różnych języków.

6

The design and implementation of a Chinese financial invoice recognition system

Ming D., Liu J., Tian J.

Image Processing & Communications

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2002

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Vol. 8, no 1

33-43

EN

This paper designs and implements a financial invoice recognition system based on the features of the Chinese financial invoice. By using the linear whole block moving method in each vertical segment, a new fast algorithm is put forth to detect and rectify the slant image. To distinguish the different form types (the foundation necessary for locating the form fields, filtering the form lines, etc.), several representative form features are discussed and an invoice-type features library is built by using a semi-automatic machine study method. On the basis of the recognized invoice type, real invoice form is re-oriented against the corresponding blank form according to the invoice type feature, solving the problem of adhesion of characters and form lines, as well as the problem of characters segmentation and recognition. Based on the financial Chinese invoice image feature, a mutual rectification mechanism founded on the recognition results of financial Chinese characters and Arabic numerals is put forward to raise the recognition rate. Finally, the experimental results and conclusions are presented.

7

Image processing and database architecture for Intelligent Transportation Systems

Anagnostopoulos C., Anagnostopoulos J., Kayafas E., Loumos V.

Image Processing & Communications

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2002

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Vol. 8, no 2

93-103

EN

This paper presents in detail all the relevant components required for the design of a real-time traffic Intelligent Transportation System (ITS). Specifically, the paper addresses analytically hardware and software issues such as the image acquisition module, the image processing routines, the OCR engine using Artificial Neural Network (ANN) technology and the database management system (DBMS). The image-processing algorithm, which is the software core of the system, works in different natural backgrounds, angles of vision and a wide range of illumination conditions and additionally it is plate-format independent. Following image processing, the OCR engine presented high level of accuracy and the total performance of the identification system is 92,5% on the basis of ITS standards. The benefits of such systems and their potential applications are discussed in the final section, where situations in which non-trivial problems can be solved by using such an artificial vision system are highlighted.