The company has core competencies in the areas of image processing, computer vision, bioimage analysis, data hiding and image registration. In the past four years, Mayachitra has rapidly grown into a leader in image informatics and now employs nine full-time engineers, most of them Ph.D.s. This team has extensive experience in image processing, computer vision, machine learning, scientific computing, and multimedia databases. Our key technology area include:

  • Large scale image/video database management
  • Automated image labeling and classification
  • Advanced image and video registration
  • Quantitative analysis of biological images
  • Video activity recognition
  • Visual & activity content-based search
  • Search relevance feedback
  • Video saliency detection
  • Robust segmentation
  • High dimensional descriptor indexing
  • Visual content based search

    Visual & activity content-based search

    Mayachitra has created state-of-the-art methods for content-based search of large scale image and video databases: Visual Indexing and Search (VIS™). Mayachitra has numerous proprietary methods and implementations for extracting compact feature vector representations from images and video, and comparing these representations effectively and quickly. Currently a low level visual descriptor is integrated into Mayachitra imago that leads to image content-based search. View VIS™ technology in action

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    Visual content based search

    Advanced image and video registration

    Mayachitra provides an advanced image/video registration designed to register unordered sets of images and video streams in a completely automatic manner. AIPR (Advanced Image Pair Registration) and VideoReg employ state-of-the-art, proprietary algorithms that are designed to cope with all sort of images, including video streams obtained from unmanned aerial vehicles (UAVs), satellite imagery, and biological images. Our technology offers unprecedented robustness and accuracy in presence of large distortions, scale variations, and even across different sensor modalities.

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