LAB: Grayscale Image Segmentation

Count nuts and bolts

LAB: Grayscale Image Segmentation

Segment and count each nuts and bolts

I. Introduction

Goal: Count the number of nuts & bolts of each size for smart factory

There are 2 different size bolts and 3 different types of nuts. You are required to segment the object and count each parts

Download the test image

• Bolt M5

• Bolt M6

• Square Nut M5

• Hexa Nut M5

• Hexa Nut M6

After analyzing histogram, applying thresholding and morphology, we can identify and extract the target objects from the background by finding the contours around the connected pixels.

II. Procedure

You MUST include all the following in the report. Also, you have to draw a simple flowchart to explain the whole process

• Apply appropriate filters to enhance image

• Explain how the appropriate threshold value was chosen

• Apply the appropriate morphology method to segment parts

• Find the contour and draw the segmented objects.

  • For applying contour, see Appendix

• Count the number of each parts

Expected Final Output

image

III. Report

You are required to write a concise lab report and submit the program files.

Lab Report:

• Show what you have done with concise explanations and example results of each necessary process

• In the appendix, show your source code.

• You must write the report in markdown file (*.md),

  • Recommend (Typora 0.x < 1.x)

  • When embedding images

    Option 1) If you are using local path images: You must include local image folder with the report in zip file

    Option 2) Use online link for images.

• Submit in both PDF and original documentation file/images

• No need to print out. Only the On-Line submission.

Source Code:

• Zip all the necessary source files.

• Only the source code files. Do not submit visual studio project files etc.

Appendix

Tip: (contour_demo.cpp)

// OpenCV - use findCountours function

C++: void findContours (InputOutputArray image, OutputArrayOfArrays contours, int mode, int method, Point offset=Point())

C++: void drawContours(InputOutputArray image, InputArrayOfArrays contours, int contourIdx, const Scalar& color, int thickness=1, int lineType=8, InputArrayhierarchy=noArray(), int maxLevel=INT_MAX, Point offset=Point() )

// Example code
// dst: binary image
 vector<vector<Point>> contours;
 vector<Vec4i> hierarchy;

  /// Find contours
 findContours( dst, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
  
 /// Draw all contours excluding holes
 Mat drawing( dst.size(), CV_8U,Scalar(255));
 drawContours( drawing, contours, -1, Scalar(0), CV_FILLED);
   
 cout<<" Number of coins are ="<<contours.size()<<endl;
 
 for( int i = 0; i< contours.size(); i++ )
 {
      printf(" * Contour[%d] -  Area OpenCV: %.2f - Length: %.2f \n", i, contourArea(contours[i]),                          arcLength( contours[i], true ) );       
 }

LAB Submission Instruction

Please read LAB Report Instruction