This document outlines a quality control project that uses image processing to identify faulty bolts on a conveyor belt. It includes an overview of the project requirements and specifications, design aspects like the hardware components and software used. Block diagrams and a flowchart illustrate the process workflow. The software implementation section describes various Matlab functions used for image processing tasks like preprocessing, feature extraction and matching. Finally, the document provides a schedule and references.
Initial Introduction of Image processing is included in these slides which contain 1. Introduction of Image Processing
2.Elements of visual perception
3. Image sensing and Quantization
4.A simple image formation model
5.Basic concept of Sampling and Quantization
Reader will find it easy to understand the topics described here in slides . A detailed description of each topic illustrated here.
Please read and if you like do comments also.... Thanks
COM2304: Introduction to Computer Vision & Image Processing Hemantha Kulathilake
At the end of this lesson, you should be able to;
Describe image.
Describe digital image processing and computer vision.
Compare and Contrast image processing and computer vision.
Describe image sources.
Identify the array of imaging application under the EM Image source.
Describe the components of Image processing system and computer vision system.
A Biometric Approach to Encrypt a File with the Help of Session KeySougata Das
The main objective of this work is to provide a two layer authentication system through biometric (face) and conventional session based password authentication. The encryption key for this authentication will be generated with the combination of the biometric key and session based password.
Initial Introduction of Image processing is included in these slides which contain 1. Introduction of Image Processing
2.Elements of visual perception
3. Image sensing and Quantization
4.A simple image formation model
5.Basic concept of Sampling and Quantization
Reader will find it easy to understand the topics described here in slides . A detailed description of each topic illustrated here.
Please read and if you like do comments also.... Thanks
COM2304: Introduction to Computer Vision & Image Processing Hemantha Kulathilake
At the end of this lesson, you should be able to;
Describe image.
Describe digital image processing and computer vision.
Compare and Contrast image processing and computer vision.
Describe image sources.
Identify the array of imaging application under the EM Image source.
Describe the components of Image processing system and computer vision system.
A Biometric Approach to Encrypt a File with the Help of Session KeySougata Das
The main objective of this work is to provide a two layer authentication system through biometric (face) and conventional session based password authentication. The encryption key for this authentication will be generated with the combination of the biometric key and session based password.
At the end of this lesson, you should be able to;
describe spatial resolution
describe intensity resolution
identify the effect of aliasing
describe image interpolation
describe relationships among the pixels
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Detection and tracking of red color by using matlabAbhiraj Bohra
This program just tracks all red color objects and draws a bounding box around them. This works on the difference between frames concept. Every frame in the video is returned as an rgb image on which we can do image processing.
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.
At the end of this lesson, you should be able to;
describe Connected Components and Contours in image segmentation.
discuss region based segmentation method.
discuss Region Growing segmentation technique.
discuss Morphological Watersheds segmentation.
discuss Model Based Segmentation.
discuss Motion Segmentation.
implement connected components, flood fill, watershed, template matching and frame difference techniques.
formulate possible mechanisms to propose segmentation methods to solve problems.
Fundamental concepts and basic techniques of digital image processing. Algorithms and recent research in image transformation, enhancement, restoration, encoding and description. Fundamentals and basic techniques of pattern recognition.
AN EFFICIENT FPGA IMPLEMENTATION OF MRI IMAGE FILTERING AND TUMOUR CHARACTERI...VLSICS Design
This paper presents an efficient architecture for various image filtering algorithms and tumor characterization using Xilinx System Generator (XSG). This architecture offers an alternative through a graphical user interface that combines MATLAB, Simulink and XSG and explores important aspectsconcerned to hardware implementation. Performance of this architecture implemented in SPARTAN-3E Starter kit (XC3S500E-FG320) exceeds those of similar or greater resources architectures. The proposed architecture reduces the resources available on target device by 50%.
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
At the end of this lesson, you should be able to;
define segmentation.
Describe edge based in segmentation.
describe thresholding and its properties.
apply edge detection and thresholding as segmentation techniques.
ODF III - 3.15.16 - Day Two Morning SessionsMichael Kerr
Slide presentations delivered during morning sessions of Day Two of the California Statewide Health and Human Services Open DataFest - March 14 - 15, 2016, Sacramento, CA
India rubber-industry-forum-2016. Kartik Srinivas has a Master's degree in Mechanical Engineering from Wright State University, USA. He is a consulting mechanical engineer with extensive background and experience in product engineering using simulation technologies and mechanical testing. Kartik provides Finite Element Analysis (FEA) solutions to a broad range of industries and is well versed with material and product testing as per ASTM and ISO standards. Kartik has 7 technical papers to his credit and has been the chair of the session on automotive composites at the SAE World Congress from 2006 through 2011. He has volunteered as a reviewer for the Journal of Rubber Chemistry and Technology
At the end of this lesson, you should be able to;
describe spatial resolution
describe intensity resolution
identify the effect of aliasing
describe image interpolation
describe relationships among the pixels
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Detection and tracking of red color by using matlabAbhiraj Bohra
This program just tracks all red color objects and draws a bounding box around them. This works on the difference between frames concept. Every frame in the video is returned as an rgb image on which we can do image processing.
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.
At the end of this lesson, you should be able to;
describe Connected Components and Contours in image segmentation.
discuss region based segmentation method.
discuss Region Growing segmentation technique.
discuss Morphological Watersheds segmentation.
discuss Model Based Segmentation.
discuss Motion Segmentation.
implement connected components, flood fill, watershed, template matching and frame difference techniques.
formulate possible mechanisms to propose segmentation methods to solve problems.
Fundamental concepts and basic techniques of digital image processing. Algorithms and recent research in image transformation, enhancement, restoration, encoding and description. Fundamentals and basic techniques of pattern recognition.
AN EFFICIENT FPGA IMPLEMENTATION OF MRI IMAGE FILTERING AND TUMOUR CHARACTERI...VLSICS Design
This paper presents an efficient architecture for various image filtering algorithms and tumor characterization using Xilinx System Generator (XSG). This architecture offers an alternative through a graphical user interface that combines MATLAB, Simulink and XSG and explores important aspectsconcerned to hardware implementation. Performance of this architecture implemented in SPARTAN-3E Starter kit (XC3S500E-FG320) exceeds those of similar or greater resources architectures. The proposed architecture reduces the resources available on target device by 50%.
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
At the end of this lesson, you should be able to;
define segmentation.
Describe edge based in segmentation.
describe thresholding and its properties.
apply edge detection and thresholding as segmentation techniques.
ODF III - 3.15.16 - Day Two Morning SessionsMichael Kerr
Slide presentations delivered during morning sessions of Day Two of the California Statewide Health and Human Services Open DataFest - March 14 - 15, 2016, Sacramento, CA
India rubber-industry-forum-2016. Kartik Srinivas has a Master's degree in Mechanical Engineering from Wright State University, USA. He is a consulting mechanical engineer with extensive background and experience in product engineering using simulation technologies and mechanical testing. Kartik provides Finite Element Analysis (FEA) solutions to a broad range of industries and is well versed with material and product testing as per ASTM and ISO standards. Kartik has 7 technical papers to his credit and has been the chair of the session on automotive composites at the SAE World Congress from 2006 through 2011. He has volunteered as a reviewer for the Journal of Rubber Chemistry and Technology
PCB Faults Detection Using Image Processingijceronline
This paper reviews the digital image processing for PCB fault detection by using MATLAB software. In this project we are implementing different algorithms in sequentional manner with GUI. In this process we are giving two input images one to be inspected for errors i.e. layout of circuit which is implemented on PCB and other one is reference image or standard image of PCB. After these process we can obtained numbers of faults in any respect like hole, Breakout etc. it helps to detect the fault at primary stage of designing. Hence to improve the image quality of compared image we use sharpened process, so we get sharpen images and fault can be detected easily and it is fast and accurate .it reduce the manufacturing cost of PCB
Improving image resolution through the cra algorithm involved recycling proce...csandit
Image processing concepts are widely used in medical fields. Digital images are prone to a
variety of types of noise. Noise is the result of errors in the image acquisition process for
reconstruction that result in pixel values that reflect the true intensities of the real scenes. A lot
of researchers are working on the field analysis and processing of multi-dimensional images.
Work previously hasn’t sufficient to stop them, so they continue performance work is due by the
researcher. In this paper we contribute a novel research work for analysis and performance
improvement about to image resolution. We proposed Concede Reconstruction Algorithm (CRA)
Involved Recycling Process to reduce the remained problem in improvement part of an image
processing. The CRA algorithms have better response from researcher to use them
IMPROVING IMAGE RESOLUTION THROUGH THE CRA ALGORITHM INVOLVED RECYCLING PROCE...cscpconf
Image processing concepts are widely used in medical fields. Digital images are prone to a variety of types of noise. Noise is the result of errors in the image acquisition process for
reconstruction that result in pixel values that reflect the true intensities of the real scenes. A lot of researchers are working on the field analysis and processing of multi-dimensional images. Work previously hasn’t sufficient to stop them, so they continue performance work is due by the researcher. In this paper we contribute a novel research work for analysis and performance improvement about to image resolution. We proposed Concede Reconstruction Algorithm (CRA)
Involved Recycling Process to reduce the remained problem in improvement part of an image processing. The CRA algorithms have better response from researcher to use them.
Hardware software co simulation of edge detection for image processing system...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
AUTOMATIC IMAGE PROCESSING ENGINE ORIENTED ON QUALITY CONTROL OF ELECTRONIC B...sipij
We propose in this work a study of an image processing engine able to detect automatically the features of
electronic board weldings. The engine has been developed by using ImageJ and OpenCV libraries.
Specifically the image processing segmentation has been improved by watershed approach. After a
complete design of the automation processes, different test have been performed showing the engine
efficiency in terms of features extraction, scale setting and thresholding calibration. The engine provides as
outputs the storage of the cropped images of each single defects. The proposed engine together with the
post-processing 3D imaging represent a good tool for the management of the production quality of
electronic boards.
COMPARISON OF GPU AND FPGA HARDWARE ACCELERATION OF LANE DETECTION ALGORITHMsipij
The two fundamental components of a complete computer vision system are detection and classification.
The Lane detection algorithm, which is used in autonomous driving and smart vehicle systems, is within the
computer vision detection area. In a sophisticated road environment, lane marking is the responsibility of
the lane detection system. The warning system for a car that leaves its lane also heavily relies on lane
detection. The two primary stages of the implemented lane detection algorithm are edge detection and line
detection. In order to assess the trade-offs for latency, power consumption, and utilisation, we will
compare the state-of-the-art implementation performance attained with both FPGA and GPU in this work.
Our analysis highlights the benefits and drawbacks of the two systems.
Comparison of GPU and FPGA Hardware Acceleration of Lane Detection Algorithmsipij
The two fundamental components of a complete computer vision system are detection and classification.
The Lane detection algorithm, which is used in autonomous driving and smart vehicle systems, is within the
computer vision detection area. In a sophisticated road environment, lane marking is the responsibility of
the lane detection system. The warning system for a car that leaves its lane also heavily relies on lane
detection. The two primary stages of the implemented lane detection algorithm are edge detection and line
detection. In order to assess the trade-offs for latency, power consumption, and utilisation, we will
compare the state-of-the-art implementation performance attained with both FPGA and GPU in this work.
Our analysis highlights the benefits and drawbacks of the two systems.
3. Overview of quality control
System using Image Processing
Quality control Technology involves
Video to frame conversion
Storing features in a database
Using them to identify objects on conveyer belt
Quality control process flow :-
1. Sample Capture – digital camera
2. Feature Extraction – creation of template
3. Template Comparison –
Verification - 1 to 1 comparison
- gives yes/no decision
4. Matching – Uses different matching algorithms
4. Project Requirements :
Input : Image in JPEG format
Intel processor with 128 MB RAM
Hard Disk Space 40 MB
Web Camera
WINDOWS operating system
MATLAB 7.0
5. Specifications
The project developed uses various components.
They are as follows:
Specifications
Microcontroller
PIC18F458
OP-AMP
LM 358
Camera
Webcam
Stepper
Motor driver
ULN 2003
7. 1.Hardware
The main hardware components that are used in this project are as follows:
Hardware Aspect
(a) Microcontroller PIC18F458
(b) OP-AMP LM 358
(c)Camera Webcam
(d) Stepper motor
driver
ULN 2003
8. 2.Software
Three main softwares are used that forms the software
aspect of this project.
They are as given below:
Software Aspect
Matlab Used to write the program code
Flash magic
Used to burn the program in the
microcontroller IC
Proteaus To Create PCB Layout
11. Flowchart
START
Wait until some charector from controller as indication of
object came in front of IR sensor
Take image of Object & subtract backgrond from image
Gray level thresholing for convesion to binary & Adjust some
brightness
Dialate(D) & Erode(E) the image & subtract as(D-E) for
border detection & clear holes
Use sobel function edge detection & extrct properties for
matching ilke Form Factor, Area ,perimeter..
If image is
faulty
Send charector to controller to indicate fauly nuts came ,
oprate soleniod.
14. Various Matlab Functions To Be Used
1.Imresize
B = imresize(A, [mrows ncols]) returns image B that has the
number of rows and columns specified by [mrows ncols].
15. 2.Imadjust
J = imadjust(I,[low_in; high_in],[low_out; high_out]) maps the
values in I to new values in J such that values between low_in
and high_in map to values between low_out and high_out. We
have used an empty matrix ([]) for [low_in high_in] or for
[low_out high_out] to specify the default of [0 1].
16. 3.im2bw
BW = im2bw(I, level) converts the grayscale image I to a binary
image. The output image BW replaces all pixels in the input image
with luminance greater than level with the value 1 (white) and
replaces all other pixels with the value 0 (black). To compute the
level argument, we have used the function graythresh. If the level
is not specified im2bw uses the value 0.5.
17. 4.Dilation Operation (imdilate)
Original Image Dilated Image
In Dilation operation,the value of the output pixel is
the maximum value of all the input pixels
neighbourhood.Dilation process basically expands an
image.
18. 5.Erosion (imerode)
Erosion is opposite to that of dilation. In Erosion operation the
value of output pixel is the minimum value of all the pixels in the
input pixels neighbourhood. Basically, erosion shrinks an image.
Original image Eroded Image
19. 6.Filling up holes (imfill)
Imfill displays the binary image on the screen and lets you
define the region to fill by selecting points interactively by
using the mouse. Binary image must be a 2-D image.
Dilation-erosion Filled Up Image
20. 7.Imclearborder
IM2 = imclearborder(IM,conn) specifies the desired connectivity.
conn can have any scalar values. Imclearborder suppresses
structures that are lighter than their surroundings and that are
connected to the image border. (In other words, use this function
to clear the image border.) IM can be a grayscale or binary image.
The output image, IM2, is grayscale or binary, respectively.
21. 8.Edge Detection (Canny Operator)
It uses a multistage algorithm to detect a wide range of edges in
an image.It is the most powerful edge detector which uses
Gaussian LPF and takes first derivative.The Canny edge
detector uses a filter based on the 1st derivative of a
Gaussian.The image is smoothened using a Gaussian filter.
Original Image Edge detected Image
22. 9.Region Properties (regionprops)
Regionprops computes area, centroid and
Bounding Box. Area scalar actual number of pixels
in the scalar actually returns the distance around the
boundary of a region.
Regionprops computes the perimeter by
calculating the distance between each adjoining pair
of pixels around the border of the region. If the
images contains discontinuity regions,regionprops
returns unexpected result.
23. Results obtained using regionprops
1.For Non-faulty bolt
perimeter is :-
415.5046
Area is :-
360
Form Factor :-
0.0262
Bolt is Not Faulty
24. Results obtained using regionprops
2.For Faulty bolt
perimeter is :-
704.4823
Area is :-
603
Form Factor :-
0.0153
Bolt is Faulty
30. References
Ambarish A. Salodkar and M.M.Khanapurkar “ Recognition of Bolt
and Nut using Image Processing” International Conference on
Emerging Frontiers in Technology for Rural Area (EFITRA) 2012
Teuku Muhammad Johan, Anton Satria Prabuwono “Recognition of
Bolt and Nut using Artificial Neural Network” International
Conference on Emerging Frontiers in Technology for Rural Area
(EFITRA) 2011
Raffaella Mattone, Linda Adduci and Andreas Wolf “On-line
scheduling algorithms for improving performance of pick-and-place
operations on a moving conveyor belt” Proceedings of the 1998
IEEE International Conference on Robotics & Automation Leuven,
Belgium May 1998
31. Schedule for Semester-II
Sr.No. Job Scheduled Date
1. Presentation number 3 before
committee
30/12/2013
2. Verification of Software aspect 12/01/2014
3. Preparation of various layouts 27/01/2014
4. Functional Simulations 02/02/2014
5. Verification of Simulations 15/02/2014
6. Soldering of PCB 30/02/2014
7. Verification of Hardware and
Troubleshooting
15/03/2014
8. Presentation of final project before
committee
31/03/2014