Optical mark recognition

Abstract: A method of combined optical mark reading ("OMR") and image processing utilizes a response sheet having a grid of response positions suitable for marking and for processing by OMR and at least one response area for a response of an alphanumeric or pictorial nature, the response area encompassing at least one of the positions suitable for processing by OMR. The response sheet is scanned to detect the presence of data signifying marks at positions in the grid and the grid is sensed for marks capable of detection and reading by OMR. In response to the sensing step, an image in the response area of a response of an alphanumeric or pictorial nature is selectively captured and stored simultaneously with OMR.

Abstract: A scannable form (10) for use in an optical mark reading system has a timing track that is pre-encoded with data information known or determined prior to a respondent completing the scannable form. The data information is pre-encoded in the control mark column (12) on the scannable form by utilizing that portion of the control mark column that is not essential for conveying the scan control information associated with the scan control marks (14). The data information is encoded using data marks (20) that represent the data information in a binary or other similar coding technique. The data marks are column-aligned with the scan control marks in the control mark column.

Abstract: Optical mark recognition (OMR) is a traditional data input technique and an important human computer interaction technique which is widely used in education testing. Aimed at the drawbacks of current OMR technique, a new image-based low cost OMR technique is presented in the paper. The new technique is capable of processing thin papers and low-printing precision answer sheets. The system key techniques and relevant implementations, which include the image scan, tilt correction, scanning error correction, regional deformation correction and mark recognition, are presented. This new technique is proved robust and effective by the processing results of large amount of questionnaires.

Abstract: This paper proposes a new idea for grading multiple-choice test which is based on a camera with reliability and efficiency. The bounds of the answer sheet image captured by the camera is first allocated using Hough transform and then skew-corrected into the proper orientation, followed by the normalization to a given size. Next, the tick mark corresponding to the answer for each question can be recognized by allocation of the mask which wraps the answer area. The experimental results showed that the proposed system has achieved significant improvement in performance in terms of accuracy, reliability, and elapsed time compared with those of the conventional optical mark recognition (OMR) systems. The proposed system also demonstrated that it can also achieve high accuracy of 99.7% while using non-transoptic answer sheet paper with lower cost.