Most of the research scholars to choose their thesis work under the domain of image processing. Operates on images and results in images which improve the visibility of features and to facilitate subsequent analysis. To enhance raw images received from sources such as cameras and sensors. Image processing thesis must depend on the implementation and paper preparation.

Image Processing operations:

  • Enhancement of important image particulars by the way suppressing other information’s.
  • Image imperfections and defects are corrected.
  • Create binary representation.
  • Done performance measurements of features.


Applications of Image Processing:

  • Forensic Studies.
  • Military Applications.
  • Document Processing.
  • Non-Destructive Evaluation.
  • Graphic Arts.


Thesis Topics for Image Processing:

  • Content based Image Retrieval
  • Security
  • Intelligent Transportation System
  • Satellite Imaging
  • Forensic Image Processing


Content based Image Retreival:- Thesis Topics for Image Processing

  • Search analyzes contents according to the image not in the meta data such as keywords, tags or description associated with the image
  • Contents are may be in the form of shape, color and texture


Recent CBIR issues:-Thesis Topics for Image Processing

  • Image Blocking
  • Color and Texture Feature Derivation
  • Color Indexing


Security:-Thesis Topics for Image Processing

  • Security to be maintained by the techniques of cryptography, steganography and watermarking


Intelligent Transportation System:-Thesis Topics for Image Processing

  • Video retrieval process to be done onto the intelligent transportation system


Satellite Imaging:-Thesis Topics for Image Processing

  • Geographic Information System based concepts are developed under matlab simulation
  • Research problems taken into remote sensing input images such as SAR, RADAR, SONAR, ASTER


Forensic Image Processing:-Thesis Topics for Image Processing

  • Involves the computer restoration and enhancement of surveillance imagery
  • To maximize information extraction from surveillance imagery


Methods of Image Processing:-Thesis Topics for Image Processing

  • Adaptive Transformations
  • Watermarking
  • Sparse Representation
  • Dictionary learning


Adaptive Transformation:-Thesis Topics for Image Processing

  • Adaptive transformation method works based on classical methods and adaptive methods
  • Adaptive method constituents are stepping rule, stopping criterion and threshold estimate
  • Performances are measured by bias, precision and efficiency


Watermarking:-Thesis Topics for Image Processing

  • Embedding data into an image
  • Data must be stored in the actual pixels
  • Format may change


Sparse Representation:-Thesis Topics for Image Processing

  • Sparse signals can be exactly reconstructed from a small number of elementary signals
  • Collaborative sparse coding defined by a single point, it have more than one sparse representation with similar data fitting errors
  • Sparse representations are classified into linear representation and non-linear representation


Dictionary Learning:-Thesis Topics for Image Processing

  • Dictionary learning is to be solved by a class dependent supervised simultaneous orthogonal matching
  • NP-hard but greedy optimizations are possible
  • Compute redundant dictionary size which minimizes average non-linear approximation error

MATLAB THESIS PHD Sample Code for Curve Fitting:-

x = [1 2 3 4 5 6]; y = [5.5 43.1 128 290.7 498.4 978.67]; %data
p = polyfit(x,y,4) %get the polynomial
% Compute the values of the polyfit estimate over a finer range,
% and plot the estimate over the real data values for comparison:
x2 = 1:.1:6;
y2 = polyval(p,x2);
grid on

MATLAB THESIS PHD Sample Code for Image Retrieval using bag of features:-

Select image features for retrieval:
% Display a few of the flower images
Create bag of Features:
% Load pre-trained bagOfFeatures
Index Images:
% Create a search index
% flowerImageIndex = indexImages(flowerImageSet, colorBag, ‘SaveFeatureLocations’, false);
% Load the pre-saved index
load(‘savedColorBagOfFeatures.mat’, ‘flowerImageIndex’);

Search similar images:
% Define a query image
queryImage = read(flowerImageSet, 502);


% Search for the top 20 images with similar color content[imageIDs, scores] = retrieveImages(queryImage, flowerImageIndex);