OCR(opencv vs tesseract)
16lz
2021-01-26
opencv:
For object detection, you're just trying to figure out whether the object is in the frame, and approximately where it's located. The OpenCv features framework is great for this
tesseract:
If your documents have a fixed structured (consistent layout of text fields) then tesseract-ocr is all you need.
I found tesseract easy to use for font based OCR while OpenCV is good for recognizing hand writing.
The following steps worked well with me:
1.Obtain grayscale of image.
2.Perform canny edge detection on grayscale image.
3.Apply gaussian blur on grayscale image(store in seperate matrix)
4.Input matrices from steps 2 & 3 into SWT algorithm
5.Binarize(threshhold) resulting image.
6.Feed image to tesseract.
Please note, for step 4 you will need to build the c++ library in the link and then import into your android project with JNI wrappers. Also, you will need to do micro tweaking fo
For object detection, you're just trying to figure out whether the object is in the frame, and approximately where it's located. The OpenCv features framework is great for this
tesseract:
If your documents have a fixed structured (consistent layout of text fields) then tesseract-ocr is all you need.
I found tesseract easy to use for font based OCR while OpenCV is good for recognizing hand writing.
The following steps worked well with me:
1.Obtain grayscale of image.
2.Perform canny edge detection on grayscale image.
3.Apply gaussian blur on grayscale image(store in seperate matrix)
4.Input matrices from steps 2 & 3 into SWT algorithm
5.Binarize(threshhold) resulting image.
6.Feed image to tesseract.
Please note, for step 4 you will need to build the c++ library in the link and then import into your android project with JNI wrappers. Also, you will need to do micro tweaking fo
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