Feature Detection and Matching with Lineous Adjustment and Adaptive Thresholding

Project Code :TMMAIP366


In this work, feature matching is performed using FAST feature descriptor.


In this work, feature matching is performed using the FAST feature descriptor. The identification of image features and matching technology are key elements of the view in computer vision.

Even then, the problem remains between fast response and stable matching in real-time. We suggest a method for extracting image features and matching using image processing techniques to solve this issue. To solve this problem, we adopt rotation, contrast adjustment, and blurring for image pairs processed by medium filtering. 

Here, the FAST approach is applied for feature selection to improve the performance. The proposed method is performed on a bike dataset which is available on online sources (Google). Particularly, this paper focuses on the illumination change, image blur, and image rotation aspects.

Keywords: Image feature identification, Feature matching, Feature descriptors, Feature extraction, FAST feature.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram


Software: Matlab 2018a or above


Operating Systems:

  • Windows 10
  • Windows 7 Service Pack 1
  • Windows Server 2019
  • Windows Server 2016


Minimum: Any Intel or AMD x86-64 processor

Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support


Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation

Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space


Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

  • Introduction to Matlab
  • How to start with MATLAB
  • About Matlab language
  • Matlab coding skills
  • About tools & libraries
  • Application Program Interface in Matlab
  • About Matlab desktop
  • How to use Matlab editor to create M-Files
  • Features of Matlab
  • Basics on Matlab
  • What is an Image/pixel?
  • About image formats
  • Introduction to Image Processing
  • How digital image is formed
  • Importing the image via image acquisition tools
  • Analyzing and manipulation of image.
  • Phases of image processing:
    • Acquisition
    • Image enhancement
    • Image restoration
    • Color image processing
    • Image compression
    •  Morphological processing
    • Segmentation etc.,
  • How to extend our work to another real time applications
  • Project development Skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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