OCR-text from image

  • OCR-text from image
  • OCR-text from image
  • OCR-text from image
  • OCR-text from image

Detailed App Info:

  • Last Changed:Time:
  • Current Version:Version: 1.0
  • Device Type:Device: iPhone Ready
  • Category:Category: Productivity
  • iTunes Seller:Seller:
  • Download Size:App Size: 97.82 MB

Application Description

Twitter:
Google:
Facebook:
OCR-text from image is useful and powerful tool that can recognize and extract text from document image.

OCR,short for Optical character recognition,is the mechanical or electronic conversion of scanned images of handwritten, typewritten or printed text into machine-encoded text.

It is widely used as a form of data entry from some sort of original paper data source, whether documents, sales receipts, mail, or any number of printed records.

Features:
1.Extract text from document image
2.Support image format including TIF, JPEG, PNG, BMP, GIF
3.Higher efficiency,higer accuracy and less time
4.Support 29 Languages (English/German/French/Russian/Dutch/Italian/Spanish/Japanese/Chinese Simplified/Chinese Traditional/Korea/Indonesian/Swedish/Romanian/Slovenia/Serbian/Turkish/Italian/Hungarian/Greek/Ukrainian/Slovakian/Finnish/Taglog/Portuguese/Bulgarian/Latvian/Polish/Czech/Catalan)

Simpler steps to get text from image
1.Click "Choose File" to open the image or directly drag to image preview.
2.Drag slider to adjust some parameters(scale,contrast,gammar) under image preview to improve image quality if needed.
3.Select the language of text in the image.
4.Click "OCR" to recognize text from image.
5.See the result in the text view and save them as a file to a destination folder.

Requirements

Your mobile device must have at least 97.82 MB of space to download and install OCR-text from image app. OCR-text from image is available on iTunes for $34.99

If you have any problems with installation or in-app purchase, found bugs, questions, comments about this application, you can visit the official website of Xiuhui Cheng at http://lemaika.com.

Copyright © lemaika