MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641048259 A) filed by Rns Institute Of Technology; Dr. K Manjunatha; Dr. Akshay Arjun; S A Shwetha; Dr. C Pandurangappa; and Dr. Shidaling Matteppanavar, Bengaluru, Karnataka, on April 15, for 'fe-doped cobalt chromite nanostructured composition and method for high-resolution daylight visualization and automated minutiae mapping of latent fingerprints.'
Inventor(s) include Dr. K Manjunatha; Dr. Akshay Arjun; S A Shwetha; Dr. C Pandurangappa; and Dr. Shidaling Matteppanavar.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a nanostructured material system and associated method for the visualization and automated analysis of latent fingerprints under ambient lighting conditions. More specifically, the invention discloses the synthesis and application of iron-doped cobalt chromite nanoparticles, wherein controlled incorporation of iron ions modifies the structural and surface characteristics of the spinel matrix, resulting in enhanced interaction with fingerprint residues. The Fe-doped nanoparticles are utilized as a fingerprint development agent in a powder-based application, enabling efficient adherence to moisture, oil, and organic components present in latent fingerprints. Owing to their improved surface reactivity and optical response, the developed fingerprints exhibit superior ridge-valley contrast and structural clarity when observed under natural daylight, thereby eliminating the need for ultraviolet or specialized illumination sources. The developed fingerprint images are subsequently subjected to digital processing using OpenCV-based image analysis techniques. The processing workflow includes image normalization, segmentation, orientation estimation, ridge enhancement through directional filtering, binarization, and skeletonization, followed by extraction of minutiae features. The system enables accurate identification of key fingerprint characteristics, including ridge endings and bifurcation points, supporting reliable biometric recognition. The proposed invention provides significant advantages over conventional systems, including improved visualization efficiency, enhanced ridge definition, reduced background interference, and compatibility with accessible computational tools. The integration of Fe-doped nanomaterial-assisted fingerprint development with automated image processing establishes a robust, cost-effective, and scalable platform for forensic investigation, biometric authentication, and security applications."
Disclaimer: Curated by HT Syndication.
