OPENCV stands for Open Source Computer Vision Library. OPENCV projects contains various computer vision functions. We provide openCV PROJECTS which composed of various computer vision algorithms with open source based library. We developed more than 90+ openCV projects with various real time applications and IEEE papers.  OpenCV Tutorial supports various languages such as python, java, C, C+ +. We implement and describe openCV in various cross platform with OS such as IOS, Linux, Mac OS X, and android. We guide M.Tech students to develop projects in Open CV under various applications.


Characteristics of OPENCV Projects:

We adopt the following characteristics in academic projects are:

  • Image Processing: It composed of histogram, sampling, color conversion, morphological operation, interpolation, corner detection and filtering.
  • Dynamic Data Structures: Provide various data structure such as sets, lists, trees, graphs and queue.
  • Basic GUI: GUI provides image or video, keyboard and mouse handling.
  • Image Labeling: It composed of line, conic, polygon and text drawing.
  • Camera Calibration: It consists of fundamental matrix, estimation of homograph, find and tracking calibration patterns.

Uses of OPENCV Projects:

We listed the uses of openCV  Projects are:

  • Security systems.
  • Motion structure in movies.
  • Robotics and safety monitoring.
  • Automatic driver assistance system.
  • Search and retrieval of video or image.

We implement universal toolbox in openCV for research and development in computer vision. We provide openCV as modular structure contains package with various shared or static libraries.


Modules of Opencv Projects:

We describe following modules in final year projects are:

  • Video: This module composed of object tracking algorithm, motion estimation and background subtraction.
  • Gpu: We generate accelerated algorithm from various openCV modules.
  • Core: This module defines basic data structure which composed of multi dimensional array and all modules use basic functions.
  • Features2d: It composed of descriptors, matchers and salient feature detectors.
  • Objdetect: It detects pre defined classes of objects and instances.
  • Cvaux: It contains various experimental functions.
  • Imgproc: This module composed of linear and non linear image filtering, color space conversion and geometrical image transformation.


Benefits of Opencv Projects:

We provided the benefits of openCV projects are:

  • Multi core processing.
  • Portability.
  • Earn of usage from user interface.
  • Ensures heterogeneous platform.


Application of Opencv Projects:

  • Facial recognition system.
  • Ego motion estimation.
  • Mobile robotics.
  • Augmented reality.
  • Gesture recognition system.
  • Object identification.
  • Segmentation and recognition.

We described opencv projects with good quality in an efficient way.  We support students who are more interested to do projects in openCV and deploy in real time applications.