如何OCR电子邮件地址

Question

I am trying to OCR and extract the email form the images. The images are supposed to have one line of text which is the email address.

I am using EmguCV.OCR to extract the text (email address) from those images. The target is to have 100% accurate result.

We can fix the font and size of the text. For example Ariel, 12pt, so that all the images will have email written in Ariel 12pt with black on white background.

The problem is that Tesseract OCR in EmguCV is not recognizing the text properly. It recognizes only 80% of the characters accurately.

I am using preprocessing with Leptonica library.

Here are some sample images I am trying to recognize.

Is there any way to achieve the target of 100% accuracy

Answer 1

With those sample images I can suggest two ways to solve the same problem. In those images JPEG artifacts are present ( the result of lossy compression ). Because of this, the letters are becoming connected to each other (zoom in on the image in a program where you can see the actual pixels, windows photo viewer worked fine for me). TesseractOCR relies on spacing between letters (it uses connected components) to do character recognition. Have any pieces connected throws off the recognition process which means it tries to recognize the combination of "co" as one letter.

Two possible solutions:

1. I'm not sure what preprocessing steps are already being done, but you'll want to do some thresholding to removing the lighter shades on the image (disconnecting the characters). However, you have to be careful with this as it may remove more than what you want.

2. If at any time during this process you have a higher resolution image, or a non-jpeg/lossy format (ie png), then keep it in this format as you do other processing steps. Try to avoid any lossy compression that might happen. It sounds like these images don't come to you as shown above. This is the preferable solution as you wont risk losing too data.

Answer 2

I tried to recognize your images with ABBYY Cloud OCR SDK and got 100% accuracy. You can use Demo Tool to make sure of recognition accuracy.

I work for ABBYY and can give you more information about our technologies if you need.