Image to Text Converter

Use the Image to Text converter to extract text from images with our OCR (Optical Character Recognition) Software, upload your image, click convert and get the extracted text in the format that suits you best.

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About the Image to Text Converter

Our website, DailyOCR.com, has some handy tools, like the Image to Text Converter and PDF to Word Converter, that can help you out.

The Image to text converter can read text from images and PDFs and turn them into editable text. Whether you have a picture with text, a PDF document, or you want to change a PDF into a Word document, you can do it easily with this tool . We make sure the text comes out just right, but in any case a human review of the results is recommended if not necessary.

This Image to text converter can detect text in lots of different languages, more exactly, 24 most used languages so it's not just for English. Whether you're working with English, Spanish, French, or any other language that the OCR tool is currently supporting.

Using our PDF to Word converter as a registered user gives you the ability to convert PDFs into Word or DOC files in batches, in other words if you have multiple files you can easily submit them all at once to the converter via the "Upload Files" button and then you can enjoy your editable text files, however there is a limit of 15 files or 200 MB in total, last but not least, another feature that we provide for registered users is that you can opt to keep your converted files in you account an indefinite time period. This way if ever delete, lose, or your drive dies then you redownload your files from you account page.

As stated above, you need to be logged in to benefit from the Batch conversion of multiple PDF, JPG, PNG or TIFF files to editable text files, you can easily create an account clicking here, for FREE with no Credit/Debit card registration, just a simple account creation process.

How to Convert PDF to Word file

OCR Supported File Types

How does the Online OCR work?

The online OCR works like any other OCR software but the difference is that you don't need to download, install and read user guides to learn how to use the software, for some this time consuming or just simply annoying. The online service is very simple and just needs you to upload the files and it will quickly respond with a download link so you can download your editable text file of your choice.

Image Acquisition. Get high quality images or PDFs so the software can recognize the text with the highest accuracy.

The process begins with the acquisition of an image containing text. This image can be scanned from physical documents, captured through cameras, or obtained from digital sources. It is recommended to get a high quality image, noise polluted and blurry images can have a negative effect on the results for any OCR software, so to get the best results please make sure you get high quality images, scans or PDFs.

Preprocessing. Applying image enhancing techniques to further increase the quality of the image.

The acquired image may contain noise, artifacts, and variations in lighting and quality. Preprocessing techniques are applied to enhance the image quality, such as adjusting contrast, removing background noise, and sharpening edges, this greatly improves the OCR process.

Text Detection. Finding the regions of text in the image.

The regions of interest or ROI are areas of the image that contain text like, titles, paragraphs, tables, headings, pagination and even individual characters. The OCR software locates these areas within the image that likely contain text by identifying the regions where the contrast between text and background is significant, hence the requirement of high quality images.

Text Segmentation. Breaking the areas of text into smaller parts.

The detected text regions are then segmented into individual characters or words, this depends on how the converter is configured. This step involves breaking down the connected components of the text into manageable units making the character or word recognition more accurate.

Feature Extraction. Getting more information about the segmented text.

For each segmented character or word, features are extracted. These features include patterns of lines, curves, edges, and angles that help distinguish one character from another.

Character Recognition. Identifying the actual characters using OCR techniques.

OCR algorithms compare the extracted features of each character against a database of known characters and fonts. This is where machine learning and pattern recognition techniques come into play. Neural networks, Hidden Markov Models (HMM), or other algorithms are often used to match features to known characters.

Postprocessing. Improving the accuracy and removing errors from the results that are obtained.

After recognition, the OCR system may perform postprocessing steps to improve accuracy. This can involve correcting errors based on context, spell-checking, and handling ambiguous characters.

Output Generation. Creating the Word or DOC file with the recognized text.

The recognized characters are then converted into digital text format. Depending on the application, the output can be plain text, formatted text, or even structured data like tables. In our case the OCR software attempts to recreate the text format from the PDF,JPG,PNG or Tiff that are fed to the system into an editable file like Word, DOC or even an editable PDF.

Verification and Correction. Human verification of the generated files is recommended.

Human verification and correction can be integrated to review and fix any errors that the OCR software might have made during the recognition process. This way you ensure that the results are of the highest quality and keep in mind that all software is created by humans.