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7 Questions to Consider Before Looking for an Alternative OCR Technology

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7 Questions to Consider Before Looking for an Alternative OCR Technology

Is your OCR tool doing the best job? Consider these questions before switching or not.

· AI Zone ·
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Looking For An Alternative OCR Technology?

Does your OCR technology make sense of the data that is extracted?

Traditional OCR technology provides less accuracy as it does not understand what is being extracted, hence, a considerable amount of errors occur. To remove such errors, it needs manual fixing, which is time-consuming and will require significant resources.

Thinking about switching from your current data extraction technology to an intelligent one?

Here Are 7 Questions to Consider First:

1. How Accurate Is Your OCR Data Extraction?

When it comes to choosing an OCR app, accuracy is one of the most important criteria. Some OCR technologies are different from other OCR software as they work on significantly improving the accuracy of the extracted data. They achieve this by learning from existing business records and extracting data in categorical context using machine learning and NLP. Thus, some OCR technologies might fill in the missing gaps that traditional OCR engines miss and they fine-tune the extracted results.

2. How Cost-Effective and Time-Saving Is Your OCR Reader?

Most companies, even after implementing an OCR, spend a lot of time and labor on manual tasks. Others use machine learning and NLP to understand the extracted data and make sense out of it. Hence, it saves a lot of time and cost, which would otherwise be spent on manual data entry tasks.

3. Does It Auto-Classify the Documents?

When dealing with huge volumes of documents, it gets difficult to classify them as invoices, receipts, contracts, and so on. Using Natural Language Processing, some OCR technologies are capable of automatically classifying and subclassifying these documents and having them neatly stacked by different categories.

4. Does It Provide a Correction Module?

Since we encounter different types of documents, the quality of each varies. So, there are chances that the OCR application extracts wrong information from low-quality documents. Therefore, to avoid such errors in the future, other OCR technologies may provide a correction module that allows users to rectify the errors.

5. Can It Extract Information From Logos?

Receipts and invoices come in different formats. Some have the merchant names while others may have only logos instead of actual names. A deep learning-based logo detection algorithm is able to identify the merchant names across the globe even if the documents just contain logos or trademarks.

6. How Does Your OCR Scanner Handle Long Receipts?

Not all receipts are of standard size. Extracting information from longer receipts has always been a problem for traditional Optical Character Recognition platform. Other OCR tools may have the ability to implement image stitching for long receipts. A computer vision and image processing technique can stitch together individual images, each containing a partial view of the document, into a mosaic view of the entire document.

7. Can You Customize Your OCR Specifically for Different Needs?

Most of the tools are generic and may not be specific to your needs. Other OCR tools can possibly ensure the customization of the OCR specifically for different needs. Some may also provide their assistance in all phases, including pre-project consulting and on-site requirements analysis, implementation and testing, on-site deployment, and technical support.

Hence, before you get a new OCR technology or change your existing one, consider the 7 questions provided above. Analyzing requirements and a perfect fit in terms of a solution are imperative for a successful project execution.

Let us know in the comments what great OCR technologies you have tried and if they answer the questions above. 

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ocr ,nlp ,artificial intelligence ,machine learning ,deep learning

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