Optical mark recognition

To recognize an exam sheet, survey, ballot, or other completed machine-readable form, digitize it in one of the supported formats. For best results, we recommend using a scanner (a basic office scanner or a copier will be enough). If you do not have a scanner, you can simply take a picture of the form with a smartphone.

• If using a smartphone, hold it parallel to the paper and make sure the sheet is well lit with minimal glares and gradients.
• The page must cover the entire area of the photo, with all 4 black squares in the corners present on the image.

1. Initializing the recognition engine

Aspose.OMR for Java recognition engine is initialized with the recognition pattern (a file with .OMR extension), saved along with the printable form. The recognition pattern is loaded using getTemplateProcessor method of OmrEngine class:

OmrEngine engine = new OmrEngine();
TemplateProcessor processor = engine.getTemplateProcessor("pattern.omr");

Recovering a recognition pattern file

If you have lost the recognition pattern file for the completed form, simply generate it again from the form’s source code using exactly the same paper size, font, and other layout setting.

2. Recognizing OMR forms

To recognize a completed form, process its scanned image or photo through recognizeImage method of the initialized recognition engine:

OmrEngine engine = new OmrEngine();
TemplateProcessor processor = engine.getTemplateProcessor("pattern.omr");
RecognitionResult result = processor.recognizeImage("survey123.png");

The recognition method support accuracy adjustments for reliable results for different types of marks under various conditions.

3. Saving recognition results

After the recognition is finished, you can get results in the most popular data storage formats.

Saving as CSV

Comma-separated values (CSV) is a lightweight text format that uses a comma to separate values in a table-like structure. Best suited for spreadsheet applications and simple relational database tables.

To save recognition results in CSV format, call getCsv method of the recognition result object:

OmrEngine engine = new OmrEngine();
TemplateProcessor processor = engine.getTemplateProcessor("pattern.omr");
RecognitionResult result = processor.recognizeImage("survey123.png");
String csv = result.getCsv();
System.out.println(csv);

Saving as JSON

JSON is the most popular popular open standard format for describing nested data structures. Best suited for NoSQL databases or web.

To save recognition results in JSON format, call getJson method of the recognition result object:

OmrEngine engine = new OmrEngine();
TemplateProcessor processor = engine.getTemplateProcessor("pattern.omr");
RecognitionResult result = processor.recognizeImage("survey123.png");
String csv = result.getJson();
System.out.println(csv);