OMR Form Inspection by Web Camera Using Shape-Based Matching ApproachIJRES Journal
The role of computer vision system as a vital component for high quality image analysis mainly in inspection and recognition process cannot be denied. The system is developed to overcome the discrepancy and drawback from human error and high-cost peripherals. This paper proposes shape-based vision algorithm, a hierarchical template-matching approach that implemented in this system to verify the imaging and inspecting the correct answer of the Optical Mark Recognition (OMR) sheet form. An OMR answer sheet schemes with all correct answers are marked on the paper and will be used as a template for object recognition during matching process. Region of interest (ROI) is selected and filtered into grey level to extract the contour of the object. The image is then pre-processed and trained using image processing technique. A low-cost 1.3 MP web camera is used to acquire the marked OMR image for all questions together with the sequence number; this is to ensure the system can distinguish between different questions having the same answer. The student’s answer in the OMR sheet form which matched with the template will be recognized as correct. This approach result shows that the algorithm works better with detection rate and matching accuracy of more than 96%. The approach can be applied in school as teachers able to know the effect of learning and teaching easily and quickly or any other areas which apply shape in their application.
OMR Form Inspection by Web Camera Using Shape-Based Matching ApproachIJRES Journal
The role of computer vision system as a vital component for high quality image analysis mainly in inspection and recognition process cannot be denied. The system is developed to overcome the discrepancy and drawback from human error and high-cost peripherals. This paper proposes shape-based vision algorithm, a hierarchical template-matching approach that implemented in this system to verify the imaging and inspecting the correct answer of the Optical Mark Recognition (OMR) sheet form. An OMR answer sheet schemes with all correct answers are marked on the paper and will be used as a template for object recognition during matching process. Region of interest (ROI) is selected and filtered into grey level to extract the contour of the object. The image is then pre-processed and trained using image processing technique. A low-cost 1.3 MP web camera is used to acquire the marked OMR image for all questions together with the sequence number; this is to ensure the system can distinguish between different questions having the same answer. The student’s answer in the OMR sheet form which matched with the template will be recognized as correct. This approach result shows that the algorithm works better with detection rate and matching accuracy of more than 96%. The approach can be applied in school as teachers able to know the effect of learning and teaching easily and quickly or any other areas which apply shape in their application.
Quick NC simulation & verification for high speed machiningLiu PeiLing
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Finger Vein Detection using Gabor Filter, Segmentation and Matched FilterEditor IJCATR
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Offline signature identification using high intensity variations and cross ov...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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Document Analysis and Recognition (DAR) aims to extract automatically the information in the document and also addresses to human comprehension. The automatic processing of degraded
historical documents are applications of document image analysis field which is confronted with many difficulties due to the storage condition and the complexity of the script. The main interest
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Gaussian blur, Mean and Bilateral filter, with different mask sizes. This is followed by
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thresholding algorithm. In the second phase Segmentation is carried out using Drop Fall and
WaterReservoir approaches, to obtain sampled characters, which can be used in later stages of
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for Median filter, 2x2 mask size for Gaussian blur, 4x4 mask size for Mean and Bilateral filter.
The system can effectively sample characters from enhanced images, giving a segmentation rate of 85%-90% for Drop Fall and 85%-90% for Water Reservoir techniques respectively
Review of Various Image Processing Techniques for Currency Note AuthenticationIJCERT
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The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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Numerical Control (NC) machining is the cutting edge of modern manufacturing technology. NC errors could break cutter edges, destroy work pieces and even damage the machine tool. In recent years, more and higher speed cutting is applied in the industry due to the advancement of machine tool technology and the demand of shorter production time. However, checking the NC codes for high speed machining is difficult due to the lack of information on material removal rate and the large size of NC blocks. In this paper, a novel high speed NC simulation method in an extended Z-map approach is presented, which offers higher simulation accuracy of the resulted geometry and with reasonable cutting load calculation. In conclusion the authors propose the pervasive manufacturing modeling and simulation for multi machining and layered manufacturing processes.
Presented by Rida Khan,Safa Aamir & Shehrbano Lakhanie, this is a very precise the powerful presentation on working principals of OCR, OMR and Track Ball.
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The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
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Omr scanner vs image only scanners with ocr software
1. OMR Scanner VS Image Only Scanners with OCR Software
1. Image Only Scannerswith OCR Software cannot do OMR Mark
Discrimination since they don't use ScanTools Plus to process the
exams.
2. The image only scanners with the OCR Software solution would
use a pixel count approach for OMR that will create errors when
erasures are on the sheet. This approach sets a level of 'fill' for the
bubble, say 10% which would be interpreted as a 'hit' for the
answer. If there is an erasure on the sheet, and the pixel count for
that bubble is 10%, they have a double 'hit', so this results in an
error. To overcome this inaccuracy, their solution is to send all
multiples to the editing operators causing a lot more editing labor,
not to mention to the inaccurate information.
3. Because of using image scanners, so they do everything postscanning which means OMR as well as Constructed Response is
processed from an Image File (this is NOT true OMR), but we do
true OMR in real-time for accuracy and speed.
4. They don't plan to use drop-out colors on the forms to save cost,
but with no drop out color for the answer bubbles, there is less
accuracy because the system may conclude the non-drop out
printing (black) is a mark, causing additional errors. In high stakes
situations, this erroneous information would be cause for high
visibility (as in TV and Newspaper) exposure.
5. If, during scan, the document has a fold-over or double sheet
feed, they will not know this during the scanning process, unlike
our system which shuts down should these faults happen. This
means that they will have to locate the mis-scanned document,
which could be scanned days before, and re-scan causing lost
time, extra labor and decreased accuracy.
2. 6. In addition, they risk skewing of the sheets as they are fed through
the image only scanners. This will cause significant errors. The
feed mechanism of the image only scanners is not the same as the
feed mechanism of the OMR scanners.
We have spent 2 years changing the feeding mechanism design to
eliminate skewing of the sheets, resulting in very high accuracy.
No image only scanners have our proprietary feed design and the
mechanism used in image only scanners can cause skewing errors,
up to 7% in some cases, resulting in corrupt data and enormous
editing time.
7. The feed rollers used in image only scanners will transfer pencil
graphite from the sheet being scanned to subsequent sheets
which can easily be read as a mark. Scantron Engineering changed
feed roller material and density to eliminate this graphite transfer
problem. As you can imagine, when pencil graphite is transferred
to the following sheets, and read as a mark when there really is no
mark intended, high stakes testing results are at serious risk.
8. The image only scanner doesn't know if there is an error until 3
sheets after the sheet is fed - much too late to do anything about
the error due to scanner buffering design.
9. In image only scanners there can be no information about the
specific sheet being processed because the mechanical distance
between the read station (or read head) and the printer is less
than 2 inches which does not allow time for real time processing
and then to print on the exam form as it goes through the
scanner. We validate the scanning process for each sheet by
printing on them during scan eliminating double scanning, and this
also documents that the sheet has been scanned for legal
requirements in high stakes tracking or validation situations.
3. Accuracy
Speed
White Space around
bubble
Timing Marks
mark discrimination
Easy to use
Capture Data
sheets Skewing
OMR Scanners
Consistently 99.9+ %
Up to 250
pages/minute
form can have the
bubbles very close
together, making it
possible to collect
more data in the same
space.
Need Timing marks
Image Only Scanners
Up to 99.9% with
editing
Up to 120
pages/minute
form needs to have
more “white space”
around the bubbles.
Don’t need Timing
mark
can perform mark
cannot perform mark
discrimination,
discrimination.
thereby being able to Multiple
determine erasures
marks in an area,
from darker marks
when not allowed, will
be flagged as potential
problems.
More easy and can be Less easy and should
left unattended
have operator to take
decision about
potential problems
Can capture much
Capture less data in
more data on an OMR
one form coz you
form reducing paper
should leave more
costs.
“white space” around
the bubbles.
very high accuracy by
Less accuracy and
eliminate skewing
cause significant errors