A free opensource Android app to extract text from images using OCR technology.
- works offline (without Internet access)
- works on all versions of Android; from Android 6 up to Android 14 (the latest version release)
- get image from gallery or from Camera for extracting text
- crop image before OCR processing
- share image into IMG2TXT app to extract text from it
- app UI supports Arabic & English
- app supports extracting Arabic & English languages
- app supports extracting Arabic+English text from the same image
- Use three OCR engines (ML Kit -> Google Vision -> Tesseract OCR)
- color-coded confidence/accuracy extracted text
- +80% -> white/black
- 50-79% -> purple
- -50% -> red
- let the user choose the text language before processing
- show the newlines in the result text
- ability to edit extracted text
- ability to copy extracted text
Install the img2txt app from Google Play: https://play.google.com/store/apps/details?id=com.softwarepharaoh.img2txt
Google Play : "This App Bundle contains native code, and you've not uploaded debug symbols. We recommend you upload a symbol file to make your crashes and ANRs easier to analyze and debug. Learn More". I documented the fix on my tech blog here.
- Old Codebase
- use onActivityResult (modern code)
- use general/universal openUrl() method/function
- better way of cropping images
- share image into IMG2TXT app to extract text from it
- translations (English & Arabic), default is English
- About Me
rate us on Google Play(removed)- link to Google Play
- v2.5.1
- first opensource version release is v2.5.1 on April 21st, 2024
- support Android 6 (Marshmallow) (SDK 23)
- support Android 7
- support Android 8
- support Android 9
- support Android 10
- support Android 11
- support Android 12
- support Android 13
- v2.6.0
- support Android 14 (SDK 34)
- show thresholded/cleaned image (created by Tesseract)
- v2.7.0
- release v2.7.0 on May 29th, 2024
- show bounding rectangles/boxes around each recognized word
- v2.8.0
- image to text OCR app release v2.8.0 on May 31st, 2024 with enhanced user experience and bug fixes.
- simplify app UI layout
- new simpler theme
- show alert/notice if the mean_confidence of result text is less than 60%
- on-device Tesseract OCR (English & Arabic models)
- on-device Google vision API (latin scripted languages)
- on-device ML Kit (latin scripted languages)
- in case of Arabic language or both (Arabic+English), use Tesseract OCR
- fallback strategy in case of English language is ML Kit -> Google Vision -> TesseractOCR
- color-coded confidence/accuracy of the result text from ML Kit & Tesseract OCR
- prompt the app user to choose the language of text on the image before processing it
- customize crop-screen
- make result/extracted text editable
- add line breaks (newline) in extracted text (ML Kit & Tesseract OCR)
- v2.9.0
- support Android 15 (SDK 35)
- save OCR history (aka : Detailed scanned images history)
- v2.10.0
- fix: make sure OCR history is saved in local db
- feature: add reward ad (to collect points)
- ui: add coins count
- add 3 points every day
- 1 image scan consumes 1 point
- watch reward ads to gain points
- save points in sharedPreferences
- upgrade Tesseract4Android lib
- Next Version
- rewrite app in Jetpack Compose
- batch processing (in bulk)
- PDF -> Images.foreach(ocr)
- expose more functions to Java : cpp files in
tesseract4android/src/main/cpp/tesseractand java files intesseract4android/src/main/java/com/googlecode/tesseract/androidmust be modified/added. - support Hindi ( Indian language )
- support Farsi ( Persian language )
- save extracted text as PDF
- choose more than one image to OCR
- pre-process image with thresholding for more clarity and better results/accuracy/extracted text
- Ability to edit image before/after running OCR on it (manual)
- Pre-Recognize Library - library with algorithms for improving OCR quality.
- using Tesseract in Python with OpenCV pre-processing
public Bitmap convertGray(Bitmap bitmap3) {
colorMatrix = new ColorMatrix();
colorMatrix.setSaturation(0);
ColorMatrixColorFilter filter = new ColorMatrixColorFilter(colorMatrix);
Paint paint = new Paint();
paint.setColorFilter(filter);
Bitmap result = Bitmap.createBitmap(bitmap3.getWidth(), bitmap3.getHeight(), Bitmap.Config.ARGB_8888);
Canvas canvas = new Canvas(result);
canvas.drawBitmap(bitmap3, 0, 0, paint);
return result;
}
/**
* Binarization
*
* @param tmp Binarization threshold Default 100
*/
private Bitmap binaryzation(Bitmap bitmap22, int tmp) {
// Get the width and height of the image
int width = bitmap22.getWidth();
int height = bitmap22.getHeight();
// Create a binary image
Bitmap bitmap;
bitmap = bitmap22.copy(Bitmap.Config.ARGB_8888, true);
// Traverse the original image pixels and perform binarization processing
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
// Get the current pixel value
int pixel = bitmap.getPixel(i, j);
// Get the value of the alpha channel
int alpha = pixel & 0xFF000000;
// Get the value of Red
int red = (pixel & 0x00FF0000) >> 16;
// Get the value of Green
int green = (pixel & 0x0000FF00) >> 8;
// Get the value of Blue
int blue = pixel & 0x000000FF;
if (red > tmp) {
red = 255;
} else {
red = 0;
}
if (blue > tmp) {
blue = 255;
} else {
blue = 0;
}
if (green > tmp) {
green = 255;
} else {
green = 0;
}
// The optimal pixel value is calculated by weighted average algorithm.
int gray = (int) ((float) red * 0.3 + (float) green * 0.59 + (float) blue * 0.11);
// Set the image to black and white
if (gray <= 95) {
gray = 0;
} else {
gray = 255;
}
// Get the new pixel value
int newPiexl = alpha | (gray << 16) | (gray << 8) | gray;
// Assign pixels to the new image
bitmap.setPixel(i, j, newPiexl);
}
}
return bitmap;
}
private Runnable runnable = new Runnable() {
@Override
public void run() {
final Bitmap bitmap_1 = convertGray(BitmapFactory.decodeFile(path));
baseApi.setImage(bitmap_1);
result = baseApi.getUTF8Text();
baseApi.recycle();
handler.post(new Runnable() {
@Override
public void run() {
imageView2.setImageBitmap(bitmap_1);
textView.setText(result);
dialog.dismiss();
}
});
}
};