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Akhmad Hendriawan, S.T., M.T.
NIP. 197501272002121003
Advisor 1
D4 ELECTRICAL ENGINEERING PROGRAM
DEPARTMENT OF ELECTRICAL ENGINEERING
ELECTRONIC ENGINEERING POLYTECHNIC INSTITUTE OF SURABAYA
(EEPIS)
PEANUT SORTING TOOL USING IMAGE
PROCESSING
FINAL PROJECT WORKSHOP
13-05-2022
Present by :
M.Alfian Hilmi
NRP.1110181048
Budi Nur Iman,S.Si.,M.Kom
NIP. 196912311995011001
Advisor 2
Population
Formulation Of The Problem
Purpose Of The Final Project
Scope Of The Problem
System Planing
Result
Future plan
TABLE OF CONTENTS
1
2
3
4
5
6
FORMULATION OF THE
PROBLEM
Making a tool that is able to identify the quality of
nuts and be able to sort them to separate them
Identify the shape of various qualities of peeled
peanuts
Sorting nuts by quality
PURPOSE AND BENEFIT OF
PROJECT
BENEFIT
Making a tool that is able
to identify the quality of
nuts with image processing
and be able to sort them
01 Make it easier for peanut-based food
producers to improve the quality and
quality of their food
02 improve productivity efficiency and
quality
PURPOSE
SCOPE OF
PROBLEM
Statehood
peanuts shape and color as
parameters
peanuts will be processed one by
one
SYSTEM PLANNING
FLOWCHART WORKING TOOL SYST
Software block diagram
SYSTEM PLANNING
webcam
Raspberi pi 4
model b
PCA9685 servo
driver
Servo
Desain konveyor
METHOD
 Gray Level Co-occurrence Matrix (GLCM)
is athe method used for texture
analysis/feature extraction. GLCMis a matrix
that describes the frequency of occurrence ofa
pair of two pixels with a certain intensity in a
distance and directionspecified in the image.
This method is quite frequentused because
the level of accuracy is quite high
METHOD
 KNN is a classification algorithm that classifies based on
the closest distance to other objects (neighbors). The purpose
of this study is to prove the weakness of the KNN method
and the extraction of RGB color features with certain
characteristics. The first experiment was carried out on two
objects with similar shapes but with a striking color on one
side of the object.
Future plan
Optimize the program
improving sorting mechanism
Integrate software & hardware
THANK
YOU

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pptPA-1110181048-m.alfian H.pptx

  • 1. Akhmad Hendriawan, S.T., M.T. NIP. 197501272002121003 Advisor 1 D4 ELECTRICAL ENGINEERING PROGRAM DEPARTMENT OF ELECTRICAL ENGINEERING ELECTRONIC ENGINEERING POLYTECHNIC INSTITUTE OF SURABAYA (EEPIS) PEANUT SORTING TOOL USING IMAGE PROCESSING FINAL PROJECT WORKSHOP 13-05-2022 Present by : M.Alfian Hilmi NRP.1110181048 Budi Nur Iman,S.Si.,M.Kom NIP. 196912311995011001 Advisor 2
  • 2. Population Formulation Of The Problem Purpose Of The Final Project Scope Of The Problem System Planing Result Future plan TABLE OF CONTENTS 1 2 3 4 5 6
  • 3. FORMULATION OF THE PROBLEM Making a tool that is able to identify the quality of nuts and be able to sort them to separate them Identify the shape of various qualities of peeled peanuts Sorting nuts by quality
  • 4. PURPOSE AND BENEFIT OF PROJECT BENEFIT Making a tool that is able to identify the quality of nuts with image processing and be able to sort them 01 Make it easier for peanut-based food producers to improve the quality and quality of their food 02 improve productivity efficiency and quality PURPOSE
  • 5. SCOPE OF PROBLEM Statehood peanuts shape and color as parameters peanuts will be processed one by one
  • 6. SYSTEM PLANNING FLOWCHART WORKING TOOL SYST Software block diagram
  • 7. SYSTEM PLANNING webcam Raspberi pi 4 model b PCA9685 servo driver Servo Desain konveyor
  • 8. METHOD  Gray Level Co-occurrence Matrix (GLCM) is athe method used for texture analysis/feature extraction. GLCMis a matrix that describes the frequency of occurrence ofa pair of two pixels with a certain intensity in a distance and directionspecified in the image. This method is quite frequentused because the level of accuracy is quite high
  • 9. METHOD  KNN is a classification algorithm that classifies based on the closest distance to other objects (neighbors). The purpose of this study is to prove the weakness of the KNN method and the extraction of RGB color features with certain characteristics. The first experiment was carried out on two objects with similar shapes but with a striking color on one side of the object.
  • 10.
  • 11.
  • 12.
  • 13. Future plan Optimize the program improving sorting mechanism Integrate software & hardware