Android-Based Text Recognition on Receipt Bill for Tax Sampling System

Rahmat, R F; Gunawan, Dani; Faza, Sharfina; Haloho, Novia Elisha; Nababan, Erna Budhiarti

doi:10.1109/iac.2018.8780416

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…Dilation thickens the fonts on receipts, while erosion makes them thinner. These processes are essential to separate characters that are too close together, or to identify glitchy fonts due to improper printing [24]. Noises are very detrimental to the accuracy of OCR on receipts because they may be detected as a symbol.…”

Section: Foreceipt Expensify Easy Expense Veryfi Dext Saldo Appsmentioning

confidence: 99%

Digitizing Receipts with OCR

Yeung,

John,

Muton

2023

IJCDS

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Receipt digitization carries numerous advantages over traditional paper receipts in terms of preservation. Saving images of receipts is a method of digitizing receipts, but managing (sorting, searching, editing, deleting, adding annotations) them is rather tedious. This paper analyzes current receipt managing applications in the market, and their approach in digitizing receipts. Other researchers' methods were also analyzed, and a pipeline to achieve receipt digitization is deduced. With a pipeline of various methods in each step, the strengths and flaws of each method were addressed. Improvements to those methods and to the overall usability of a receipt management system were proposed. The proposed methods were then developed into a usable product application.

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Section: Foreceipt Expensify Easy Expense Veryfi Dext Saldo Appsmentioning

confidence: 99%

Digitizing Receipts with OCR

Yeung,

John,

Muton

2023

IJCDS

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“…The challenge in this step is identifying the most suitable pre-processing algorithms to improve the quality of the type of images we are dealing with and the different combinations in which these algorithms are used. There is no standard combination of pre-processing techniques that would work for images taken in all conditions and according to [12], images of text taken in adverse conditions such as with shadows or noise will reduce the accuracy of text extracted from the OCR engine. Therefore, some pre-processing of the images before extracting the text can help in improving the accuracy of the output of the OCR engine [13].…”

Section: B Text Extraction and Analysi Of Billsmentioning

confidence: 99%

“…The research conducted in [14] uses a template matching algorithm to identify the desired information from the image. The combination of grey-scaling, sharpening, denoising, threshold, and smoothing conducted in [12] gives a higher accuracy compared to the other combinations of pre-processing techniques. The Pytesseract OCR engine is used in most research papers and has been proven to be highly effective but not highly effective for handwritten or low-quality images.…”

Section: B Text Extraction and Analysi Of Billsmentioning

confidence: 99%

Money Empire: Intelligent Assistant for Personal Finance Management

Balathas¹

2022

IJRASET

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Poverty, and debt are burning issues globally and especially in third-world nations such as Sri Lanka. The major contributing factor to poverty is poor personal financial planning resulting in being unable to make ends meet, forcing citizens to live mediocre lifestyles or even resort to debt or crime. Personal financial planning is one of the most crucial practices to overcome this situation namely: setting financial goals, tracking expenses, and meeting set budgets. In Sri Lanka, very few people keep track of their expenses, and a majority of those who do, follow manual methods which are error-prone and easily abandoned due to increased stress and complexity. This paper proposes a solution to automate the flow of personal finance management, requiring minimal effort from the user. The application detects SMS alerts received regarding Bank transactions and extracts transaction details. Users can easily upload their expense bills from which expense details will be fetched and processed. The app also allows users to split their bills with friends or family and track and settle their incoming and outgoing debts. Finally, the user can visualize their income and expense analysis at a glance and make better decisions to meet their financial objectives and all these features in one single application.

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“…Because manually transferring the receipt information to a computer is a laborintensive, time-consuming, less efficient, and error-prone process, automatic information recognition systems have been developed to address these limitations. For example, optical character recognition (OCR) technology [1] has been developed for enabling computers to read text images, extract information, and recognize text. OCR is widely used in various fields, such as identity card recognition [1], automatic license plate recognition [2], and receipt recognition [3].…”

Section: Introductionmentioning

confidence: 99%

“…For example, optical character recognition (OCR) technology [1] has been developed for enabling computers to read text images, extract information, and recognize text. OCR is widely used in various fields, such as identity card recognition [1], automatic license plate recognition [2], and receipt recognition [3]. An OCR system includes the following components: image input, image preprocessing, image correction, text positioning, character segmentation, and character recognition [4].…”

Section: Introductionmentioning

confidence: 99%

Automatic Receipt Recognition System Based on Artificial Intelligence Technology

2022

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In this study, an automatic receipt recognition system (ARRS) is developed. First, a receipt is scanned for conversion into a high-resolution image. Receipt characters are automatically placed into two categories according to the receipt characteristics: printed and handwritten characters. Images of receipts with these characters are preprocessed separately. For handwritten characters, template matching and the fixed features of the receipts are used for text positioning, and projection is applied for character segmentation. Finally, a convolutional neural network is used for character recognition. For printed characters, a modified You Only Look Once (version 4) model (YOLOv4-s) executes precise text positioning and character recognition. The proposed YOLOv4-s model reduces downsampling, thereby enhancing small-object recognition. Finally, the system produces recognition results in a tax declaration format, which can upload to a tax declaration system. Experimental results revealed that the recognition accuracy of the proposed system was 80.93% for handwritten characters. Moreover, the YOLOv4-s model had a 99.39% accuracy rate for printed characters; only 33 characters were misjudged. The recognition accuracy of the YOLOv4-s model was higher than that of the traditional YOLOv4 model by 20.57%. Therefore, the proposed ARRS can considerably improve the efficiency of tax declaration, reduce labor costs, and simplify operating procedures.

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Android-Based Text Recognition on Receipt Bill for Tax Sampling System

Cited by 9 publications

References 10 publications

Digitizing Receipts with OCR

Digitizing Receipts with OCR

Money Empire: Intelligent Assistant for Personal Finance Management

Automatic Receipt Recognition System Based on Artificial Intelligence Technology

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