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Automatic Pill Identifier: An Overview on Identifying,
Retrieving and Authenticating Drug-Pill
Presented by: Nidhi Joshi
Enroll no:202630290016
B.Pharm sem.7
Guided by: Ms. Kajal Pradhan
Assistant professor
(M.Pharm pharmaceutics)
Why is Automatic Pill Identifier important?
• Automatic Pill Identifier is a game-changer in the
healthcare industry, providing numerous benefits
in terms of patient safety and drug identification.
• patients can rest assured that they are taking the
right medication at the right time.
• Greatly reducing the risk of medication errors.
enables healthcare professionals to quickly and
accurately identify unknown pills.
• prevent counterfeit drugs from entering the
market, protecting patients from potentially
harmful substances.
2
Identifying
It is process of determining
the name, strength, and
other relevant information
about a medication solely
based on its visual
attributes, including its size,
shape, color, imprints, and
packaging.
Retrieving
Automatic pill identifiers often
retrieve comprehensive information
about a medication once it has
been identified. This information
may include the drug's name,
manufacturer, active ingredients,
dosage, indications,
contraindications, side effects, and
usage instructions.
Authentication
It involves verifying that the
identified medication is genuine
and not counterfeit . Some
systems may provide features or
tools to help users verify the
authenticity of a medication, such
as checking for unique packaging
identifiers.
3
 What is process of Automatic Pill Identifier?
o Automatic pill identifier is a technology that identifies and verifies the
authenticity of pills using computer vision or non-computer vision based
software.
1 Computer Vision-Based
Uses image processing algorithms to
analyze the physical characteristics
of the pill and match them with an
image in the pill database.
2
Non-Computer Vision-Based
Relies on input from the user,
which was manually entered
by user
4
• Computer Vision-Based Software:
• It involves using a camera or scanner to capture an image of
the pill, which is then analyzed by sophisticated algorithms.
• It use various features of the pill, such as its size, shape,
color, and markings, to identify it.
• This software performs function checks, threshold filtering, and
masking to accurately identify the pill under consideration.
• Computer vision offers precise and efficient pill recognition.
By analyzing color features based on HSV color profiles and
shape characteristics, we can accurately identify pills.
5
• Non-Computer-Vision-Based Software:
The non-computer vision-based process for automatic pill identification
involves the use of physical and chemical properties of pills, such as their
size, shape, color, and markings.
Characteristic Description
Shape The shape of the pill can be used to identify it.
Color The color of the pill can be used to identify it.
Imprint The imprint on the pill can be used to identify it.
6
Color
Dimension
Shape Processing
Detection
Process
Data collection
Steps to collect data
• Data Collection
.
 Photographs
Two mobile devices were used to photograph the pills at different
perspectives, distances, and lighting setups. A total of 5284
photographs were taken, with each pill photographed between ten
and twenty-five times.
 Storage and Handling
The pills were stored and handled as per pharmacological
guidelines to maintain authenticity
Variety
Pills from various categories, including rare ones, were collected to
create a complete library.400 widely used pills are used.
8
• Process
 The computer vision process relies on the OpenCV library, an open-
source computer vision and machine learning software library. It involves
the use of pre-processing techniques like edge detection and contour
approximation.
9
• Learning Mode
In the Learning Mode, the system takes a picture of a pill. Caregivers are responsible for adding
medications to the system's database using the learning mode.
• Picture
The system captures an
image of the pill and marker.
• Normalization
The image is then normalized
to a size of 1024x768.
• Profile
The system identifies the markers and
profiles the pill based on its color, size,
and shape.
01001000101001000101
011011011101010001001
001001100010010111101
11010100011010101000
100110100011111001100
001
10
Recognition Mode
 Shape Filter
The system estimates the pill's
shape and queries the database
for matching shapes.
 Size Filter
The system estimates the pill's
size and selects pills based on
their dimensions.
.
 Color Filter
The remaining subset of pills is
filtered by color to identify the
pill.
11
• Detection
Marker Locator
The system identifies the
markers to limit the
processing region.
.
Pill Identification
The system processes the form,
size, and color of the pill for
learning and recognition.
Categorization
The system categorizes
the pills and notifies the
user about the pills'
identity.
12
• The size of a pill plays a
crucial role in medication
identification. By measuring
the smallest side of the black
square housing the tablets, we
can determine the dimensions
accurately. Using this
information, we calculate the
height and breadth of each pill.
• Pill color is an important
aspect of identification. To
streamline the process, we
utilize image samples and a
discrete Look-Up Table (LUT)
with HSV color values. By
comparing each pixel inside
the pill's shape with the LUT,
we can accurately categorize
colors.
Shape Processing
• The algorithm searches for
markers and tablets within the
black square. Pre-processing
techniques like edge detection
and contour approximation are
applied. Shape comparison
with template shapes is done
using Hu-Moments.
Understanding Pill
Dimensions Decoding Pill
Colors
13
• Outcomes
No Pill Found
If no pill found, then it
is a notification to
check the pill once
again.
Multiple pills found
If multiple pills found,
then the user is asked
to identify the pill and
pick the right one
based on the picture.
One Pill Found
If one pill found, the pill's
name and indications are
displayed on the app.
.
14
i. Pillbox (by the National Library of Medicine)
ii. Drugs.com Pill Identifier
iii. GoodRx
iv. Epocrates
v. RxList Pill Identifier
vi. Medscape
vii. ID My Pill
viii.MyTherapy
ix. First Databank's Pillbox/Unbound Medicine Pill Identifier
x. Healthline Pill Identifier
• Example of some pill identifying software:
15
 Step 2:
Enter imprint
 Step 3:
Enter colour
 Step 4:
Enter shape
 Step 5:
Click on search and
find results
 Step 1:
open Drugs.com and
click on pill identifier
• How to identify the pill?
16
• Usage Scenarios for Automatic Pill Identification
Medication Check
Take a picture of your pill
and receive information
regarding dosage,
possible side effects, and
any potential drug
interactions.
Quality Control in
Pharmaceutical Industry
Identifying the nature and
integrity of the product,
manufacturing process,
packaging, and labeling of
medications.
Law Enforcement
Purposes
To investigate drug
manufacturing, drug dealing,
or possession case.
17
• Conclusion
 Automatic Pill Identifier systems are a valuable tool within the healthcare
industry, providing many benefits to healthcare professionals and patients
 Key Points
• Automatic pill identifier
technology offer a promising
solution for improving accuracy
and efficiency in pill
identification and reducing the
risk of medication error.
 Future Directions
• The future of automatic pill identifier is
promising with further improvements
in computer vision technology and a
more comprehensive pill database.
Hence, it might possible to
seamlessly identify potential threats
such as counterfeit pills in the market.
18
• References
1. Yaniv, Z., Faruque, J., Howe, S., Dunn, K., Sharlip, D., Bond, A., Perillan, P., Bodenreider, O., Ackerman, M. J., &
Yoo, T. S., The national library of medicine pill image recognition challenge: An initial report, 2016 IEEE Applied Imagery
Pattern Recognition Workshop (AIPR).
2. Vieira Neto, M. A., De Souza, J. W., Reboucas Filho, P. P., & Rodrigues, A. W. ,CoforDes: An invariant feature extractor
for the drug pill identification, 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS).
3. Crema, C., Depari, A., Flammini, A., Lavarini, M., Sisinni, E., & Vezzoli, A. , A smartphone-enhanced pill-dispenser
providing patient identification and in-take recognition, 2015 IEEE International Symposium on Medical Measurements
and Applications (MeMeA)
4. D. Ushizima, A. Carneiro, M. Souza, and F. Medeiros, “Investigating pill recognition methods for a new national library of
medicine image dataset,” in International Symposium on Visual Computing. Springer, 2015, pp. 410–419.
5. J. Yu, Z. Chen, S.-i. Kamata, and J. Yang, “Accurate system for automatic pill recognition using imprint information,” IET
Image Processing, 2015, vol. 9, no. 12, pp. 1039–1047.
6. “Drugs.com,” https://www.drugs.com/pill identification.html
7. “Pillbox,” https://pillbox.nlm.nih.gov.
8. “WebMD,” http://www.webmd.com/pill-identification/
19
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Overview on the Automatic pill identifier

  • 1. Automatic Pill Identifier: An Overview on Identifying, Retrieving and Authenticating Drug-Pill Presented by: Nidhi Joshi Enroll no:202630290016 B.Pharm sem.7 Guided by: Ms. Kajal Pradhan Assistant professor (M.Pharm pharmaceutics)
  • 2. Why is Automatic Pill Identifier important? • Automatic Pill Identifier is a game-changer in the healthcare industry, providing numerous benefits in terms of patient safety and drug identification. • patients can rest assured that they are taking the right medication at the right time. • Greatly reducing the risk of medication errors. enables healthcare professionals to quickly and accurately identify unknown pills. • prevent counterfeit drugs from entering the market, protecting patients from potentially harmful substances. 2
  • 3. Identifying It is process of determining the name, strength, and other relevant information about a medication solely based on its visual attributes, including its size, shape, color, imprints, and packaging. Retrieving Automatic pill identifiers often retrieve comprehensive information about a medication once it has been identified. This information may include the drug's name, manufacturer, active ingredients, dosage, indications, contraindications, side effects, and usage instructions. Authentication It involves verifying that the identified medication is genuine and not counterfeit . Some systems may provide features or tools to help users verify the authenticity of a medication, such as checking for unique packaging identifiers. 3
  • 4.  What is process of Automatic Pill Identifier? o Automatic pill identifier is a technology that identifies and verifies the authenticity of pills using computer vision or non-computer vision based software. 1 Computer Vision-Based Uses image processing algorithms to analyze the physical characteristics of the pill and match them with an image in the pill database. 2 Non-Computer Vision-Based Relies on input from the user, which was manually entered by user 4
  • 5. • Computer Vision-Based Software: • It involves using a camera or scanner to capture an image of the pill, which is then analyzed by sophisticated algorithms. • It use various features of the pill, such as its size, shape, color, and markings, to identify it. • This software performs function checks, threshold filtering, and masking to accurately identify the pill under consideration. • Computer vision offers precise and efficient pill recognition. By analyzing color features based on HSV color profiles and shape characteristics, we can accurately identify pills. 5
  • 6. • Non-Computer-Vision-Based Software: The non-computer vision-based process for automatic pill identification involves the use of physical and chemical properties of pills, such as their size, shape, color, and markings. Characteristic Description Shape The shape of the pill can be used to identify it. Color The color of the pill can be used to identify it. Imprint The imprint on the pill can be used to identify it. 6
  • 8. • Data Collection .  Photographs Two mobile devices were used to photograph the pills at different perspectives, distances, and lighting setups. A total of 5284 photographs were taken, with each pill photographed between ten and twenty-five times.  Storage and Handling The pills were stored and handled as per pharmacological guidelines to maintain authenticity Variety Pills from various categories, including rare ones, were collected to create a complete library.400 widely used pills are used. 8
  • 9. • Process  The computer vision process relies on the OpenCV library, an open- source computer vision and machine learning software library. It involves the use of pre-processing techniques like edge detection and contour approximation. 9
  • 10. • Learning Mode In the Learning Mode, the system takes a picture of a pill. Caregivers are responsible for adding medications to the system's database using the learning mode. • Picture The system captures an image of the pill and marker. • Normalization The image is then normalized to a size of 1024x768. • Profile The system identifies the markers and profiles the pill based on its color, size, and shape. 01001000101001000101 011011011101010001001 001001100010010111101 11010100011010101000 100110100011111001100 001 10
  • 11. Recognition Mode  Shape Filter The system estimates the pill's shape and queries the database for matching shapes.  Size Filter The system estimates the pill's size and selects pills based on their dimensions. .  Color Filter The remaining subset of pills is filtered by color to identify the pill. 11
  • 12. • Detection Marker Locator The system identifies the markers to limit the processing region. . Pill Identification The system processes the form, size, and color of the pill for learning and recognition. Categorization The system categorizes the pills and notifies the user about the pills' identity. 12
  • 13. • The size of a pill plays a crucial role in medication identification. By measuring the smallest side of the black square housing the tablets, we can determine the dimensions accurately. Using this information, we calculate the height and breadth of each pill. • Pill color is an important aspect of identification. To streamline the process, we utilize image samples and a discrete Look-Up Table (LUT) with HSV color values. By comparing each pixel inside the pill's shape with the LUT, we can accurately categorize colors. Shape Processing • The algorithm searches for markers and tablets within the black square. Pre-processing techniques like edge detection and contour approximation are applied. Shape comparison with template shapes is done using Hu-Moments. Understanding Pill Dimensions Decoding Pill Colors 13
  • 14. • Outcomes No Pill Found If no pill found, then it is a notification to check the pill once again. Multiple pills found If multiple pills found, then the user is asked to identify the pill and pick the right one based on the picture. One Pill Found If one pill found, the pill's name and indications are displayed on the app. . 14
  • 15. i. Pillbox (by the National Library of Medicine) ii. Drugs.com Pill Identifier iii. GoodRx iv. Epocrates v. RxList Pill Identifier vi. Medscape vii. ID My Pill viii.MyTherapy ix. First Databank's Pillbox/Unbound Medicine Pill Identifier x. Healthline Pill Identifier • Example of some pill identifying software: 15
  • 16.  Step 2: Enter imprint  Step 3: Enter colour  Step 4: Enter shape  Step 5: Click on search and find results  Step 1: open Drugs.com and click on pill identifier • How to identify the pill? 16
  • 17. • Usage Scenarios for Automatic Pill Identification Medication Check Take a picture of your pill and receive information regarding dosage, possible side effects, and any potential drug interactions. Quality Control in Pharmaceutical Industry Identifying the nature and integrity of the product, manufacturing process, packaging, and labeling of medications. Law Enforcement Purposes To investigate drug manufacturing, drug dealing, or possession case. 17
  • 18. • Conclusion  Automatic Pill Identifier systems are a valuable tool within the healthcare industry, providing many benefits to healthcare professionals and patients  Key Points • Automatic pill identifier technology offer a promising solution for improving accuracy and efficiency in pill identification and reducing the risk of medication error.  Future Directions • The future of automatic pill identifier is promising with further improvements in computer vision technology and a more comprehensive pill database. Hence, it might possible to seamlessly identify potential threats such as counterfeit pills in the market. 18
  • 19. • References 1. Yaniv, Z., Faruque, J., Howe, S., Dunn, K., Sharlip, D., Bond, A., Perillan, P., Bodenreider, O., Ackerman, M. J., & Yoo, T. S., The national library of medicine pill image recognition challenge: An initial report, 2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). 2. Vieira Neto, M. A., De Souza, J. W., Reboucas Filho, P. P., & Rodrigues, A. W. ,CoforDes: An invariant feature extractor for the drug pill identification, 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS). 3. Crema, C., Depari, A., Flammini, A., Lavarini, M., Sisinni, E., & Vezzoli, A. , A smartphone-enhanced pill-dispenser providing patient identification and in-take recognition, 2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) 4. D. Ushizima, A. Carneiro, M. Souza, and F. Medeiros, “Investigating pill recognition methods for a new national library of medicine image dataset,” in International Symposium on Visual Computing. Springer, 2015, pp. 410–419. 5. J. Yu, Z. Chen, S.-i. Kamata, and J. Yang, “Accurate system for automatic pill recognition using imprint information,” IET Image Processing, 2015, vol. 9, no. 12, pp. 1039–1047. 6. “Drugs.com,” https://www.drugs.com/pill identification.html 7. “Pillbox,” https://pillbox.nlm.nih.gov. 8. “WebMD,” http://www.webmd.com/pill-identification/ 19