Leadtools iOS SDK integration

Question

I checked with the sample OMR demo project, it is not able to recognize the marks (dark circles) and return appropriate results in response.

Answer 1

When posting on Stack Overflow, please adhere to all guidelines for asking a question as seen here: How do I ask a good question?

Also, please note that the LEADTOOLS SDK has it's own Support options as listed here: LEADTOOLS Technical Support

Regarding your issue with the OMR Demo, it's difficult to assist you with the issues that you are seeing without having a sample image that reproduces the problem. If you can edit your post to include the image you are trying to recognize, as well as what options you tried I will then be able to help your specific issue.

Without having your image, I can only provide you with generic OMR guidelines and tips.

Here is a link to the documentation page for using OMR in the SDK: Using OMR in LEADTOOLS

Here is an excerpt from this page that might help:

OMR options include "Frame detection options" and "Mark recognition sensitivity". For more information refer to the IOcrOmrOptions interface.

The printed frame should be at least 50 x 50 pixels in order to be recognized properly. Also, the printed frame needs to be noticeable (This is easily accomplished by setting the scanner brightness.)

"Mark recognition sensitivity" specifies how sensitive OMR will be to filling marks. (Highest, High, Low and Lowest). For example: For frames filled with small ticks, the mark recognition sensitivity should be set to the highest value. The highest value should also be set if the printed frames are empty and they should be recognized as being filled if simple marks are used. But if the application or exam requires the frames to be filled completely, the mark recognition sensitivity should be set to the lowest value.

Here is a link to the OcrOmrSensitivity documentation page: OcrOmrSensitivity Enumeration

and a screenshot of the different enumerations you can choose from:

I would suggest trying out different sensitivities with your images and see which ones work best for the type of OMR bubbles that you are trying to recognize. If this doesn't help with your specific scenario, please reply to this answer and edit your original question to include more information for your project.