Computer Vision: A Benchmark for Computer Science Thesis/Dissertations

M.Tech dissertations and assignments cannot be treated very lightly keeping in mind the importance of research at that level. There are several domains, streams or we can call it as fields for a master’s student. If we talk about computer science here, it will be a hot topic to discuss upon.

What are the best possible streams of research for a computer science student? This question keeps floating in the minds of every master student before starting their master thesis. Here we will let you know about the scope of computer vision in master thesis.

The computer vision is just next to image processing, as it is followed by the processing of image and video data. The research done in the computer vision can be taken in account to product development or patents as in vision based systems, security systems or surveillance systems.

Computer Vision projects include Robot and Computer Vision using Raspberry Pi, Image Crawlers-Search Engines, Deep Learning whereas the image processing will include the image deblurring, registration, smoothing, denoising, compression etc.

The projects in computer vision and image processing carried out with the machine learning i.e. with the support vector machines, neural networks or deep learning leads to the development of most advanced products or the artificial intelligence systems.

Within computer vision our research can include investigations into:

  • Imaging and Photogrammetric: It includes the use of high resolution cameras and their radiometric calibrations, the stereo vision systems, 3-D imaging and video, 3-D scene reconstruction from images and video, and image and video enhancement.
  • Pattern Recognition and Statistical Learning(Deep Learning)  It includes the data clustering and its classification, supervised and unsupervised learning, and high-dimensional geometry and statistics and analysis of patterns from the huge amount of data.
  • Object Detection and Recognition It will include the face detection, alignment, and tagging; video-based face recognition; and sparsity-based robust face recognition. The object classifications based on different classes and the analysis of medical images can also be concluded in this.
  • Image and Video Editing and Enhancement: This part of image processing will include the various operations on an image like denoising and deblurring of the image, novel representations for images and video, techniques for content-aware edits such as in-painting, and object removal, object classification, authentication etc.

The above mentioned research areas can be executed at SILICONMENTOR, INDIA with which the computer science students and professors will be given a technical platform as well as the research guidance in their master thesis/dissertation research  to execute and propagate it for the best possible research or  can be rolled into a product even.