scholarly journals Optimalisasi Image Thresholding pada Optical Character Recognition Pada Sistem Digitalisasi dan Pencarian Dokumen

Petir ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 1-11
Author(s):  
Ridwan Rismanto ◽  
Arief Prasetyo ◽  
Dyah Ayu Irawati
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Threshold Value ◽  
Document Image ◽  
Great Effort ◽  
Processing Stage ◽  
Image Thresholding ◽  
Optical Character ◽  
Value Sets ◽  
Readable Text

The administration activity in an institute is largerly done by using a paper based mailing and document as a media. Therefore, a great effort needs to be performed in the case of management and archiving, in the form of providing storage space through the categorizing system. Digitalization of document by scanning it into a digital image is one of the solution to reduce the effort to perform the work of archiving and categorizing such document. It also provide searching feature in the form of metadata, that is manually written during the digitalization process. The metadata can contains the title of document, summary, or category. The needs to manually input this metadata can be solved by utilizing Optical Character Recognition (OCR) that converts any text in the document into readable text storing in the database system. This research focused on the implementation of the OCR system to extract text in the scanned document image and performing optimization of the pre-processing stage which is Image Thresholding. The aim of the optimization is to increase OCR accuracy by tuning threshold value of given value sets, and resulting 0.6 as the best thresholding value. Experiment performed by processing text extraction towards several scanned document and achieving accuration rate of 92.568%.

scholarly journals Improving Optical Character Recognition Techniques

2018 ◽  
Vol 7 (2.24) ◽  
pp. 361 ◽  
Author(s):  
Nitin Ramesh ◽  
Aksha Srivastava ◽  
K Deeba
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Document Image ◽  
Text Recognition ◽  
Digital Form ◽  
Written Text ◽  
Optical Character ◽  
Research Organizations ◽  
The World

Document text recognition uses a concept called OCR (optical character recognition),which is the recognition of printed or written text characters by a computer. This involves scanning a document containing text, and converting character by character to their digital form. Thus, it is defined as the process of digitizing a document image into its constituent characters. Equipment used to obtain clearer images for analysis are cameras and flatbed scanners. Even though it’s been out in the world since 1870, the OCR technology is yet to reach perfection. This demanding nature of Optical Character Recognition has made various researchers, industries and technology enthusiasts to divulge their attention to this field. In recent times one can notice a significant increase in the number of research organizations investing their time and effort in this field. In this research, the progress, different aspects and various issues revolving in this field have been summarized. The aim is to present a scrupulous overview of various proposals, advancements and discussions aimed at resolving various problems that arise in traditional OCR.  

scholarly journals iDocChip: A Configurable Hardware Architecture for Historical Document Image Processing

2021 ◽  
Author(s):  
Menbere Kina Tekleyohannes ◽  
Vladimir Rybalkin ◽  
Muhammad Mohsin Ghaffar ◽  
Javier Alejandro Varela ◽  
Norbert Wehn ◽  
...  
Keyword(s):  
Power Consumption ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
High Accuracy ◽  
Document Image ◽  
System On Chip ◽  
Historical Documents ◽  
Optical Character ◽  
Historical Archives ◽  
On Chip

AbstractIn recent years, $$\hbox {optical character recognition (OCR)}$$ optical character recognition (OCR) systems have been used to digitally preserve historical archives. To transcribe historical archives into a machine-readable form, first, the documents are scanned, then an $$\hbox {OCR}$$ OCR is applied. In order to digitize documents without the need to remove them from where they are archived, it is valuable to have a portable device that combines scanning and $$\hbox {OCR}$$ OCR capabilities. Nowadays, there exist many commercial and open-source document digitization techniques, which are optimized for contemporary documents. However, they fail to give sufficient text recognition accuracy for transcribing historical documents due to the severe quality degradation of such documents. On the contrary, the anyOCR system, which is designed to mainly digitize historical documents, provides high accuracy. However, this comes at a cost of high computational complexity resulting in long runtime and high power consumption. To tackle these challenges, we propose a low power energy-efficient accelerator with real-time capabilities called iDocChip, which is a configurable hybrid hardware-software programmable $$\hbox {System-on-Chip (SoC)}$$ System-on-Chip (SoC) based on anyOCR for digitizing historical documents. In this paper, we focus on one of the most crucial processing steps in the anyOCR system: Text and Image Segmentation, which makes use of a multi-resolution morphology-based algorithm. Moreover, an optimized $$\hbox {FPGA}$$ FPGA -based hybrid architecture of this anyOCR step along with its optimized software implementations are presented. We demonstrate our results on multiple embedded and general-purpose platforms with respect to runtime and power consumption. The resulting hardware accelerator outperforms the existing anyOCR by 6.2$$\times$$ × , while achieving 207$$\times$$ × higher energy-efficiency and maintaining its high accuracy.

scholarly journals LANGUAGE INDEPENDENT ROBUST SKEW DETECTION AND CORRECTION TECHNIQUE FOR DOCUMENT IMAGES

2012 ◽  
pp. 111-115
Author(s):  
Neha. N
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Document Analysis ◽  
Document Image ◽  
Document Images ◽  
Novel Technique ◽  
Skew Detection ◽  
Optical Character ◽  
Correction Technique ◽  
All Optical

Document image processing is an increasingly important technology essential in all optical character recognition (OCR) systems and for automation of various office documents. A document originally has zero-skew (tilt), but when a page is scanned or photo copied, skew may be introduced due to various factors and is practically unavoidable. Presence even a small amount of skew (0.50) will have detrimental effects on document analysis as it has a direct effect on the reliability and efficiency of segmentation, recognition and feature extraction stages. Therefore removal of skew is of paramount importance in the field of document analysis and OCR and is the first step to be accomplished. This paper presents a novel technique for skew detection and correction which is both language and content independent. The proposed technique is based on the maximum density of the foreground pixels and their orientation in the document image. Unlike other conventional algorithms which work only for machine printed textual documents scripted in English, this technique works well for all kinds of document images (machine printed, hand written, complex, noisy and simple). The technique presented here is tested with 150 different document image samples and is found to provide results with an accuracy of 0.10

scholarly journals Optical Character Recognition Robot

10.29007/jx6c ◽  
2018 ◽  
Author(s):  
Deepak Vala ◽  
Umeshkumar Baria ◽  
Urvi Bhagat ◽  
Mohan Khambalkar
Keyword(s):  
Open Source Software ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Local Network ◽  
Line Of Sight ◽  
Raspberry Pi ◽  
Plain Text ◽  
Optical Character ◽  
Readable Text ◽  
Non Line Of Sight

In this paper presents optical character recognition robot (OCR) which is capable of converting image into the computer process able format, in the form of plain text using Raspberry pi and a webcam server where we can live stream video over a local network. Our ultimate goal is to find and solve the different requirements in making a web controlled robot that recognizes and converts textual messages placed in real world to the computer readable text files. Our objective is to integrate the appropriate techniques to explain and prove that such capability, using limited hardware and software capabilities. The objective of our work is to provide an internet controlled mobile robot with the capability of reading characters in the image and gives out strings of characters. In the project we will use MOTION software, which is open source software with a number of configuration options which can be changed according to our needs. Here configurations are to be made so that it allows you to view from any computer on the local network for the control of robot in non-line of sight areas.

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