Biometric technologies are automated methods of verifying or recognizing. This work is particularly targeted towards the SURF,HARRIS and MSER calculations for biometric fingerprint calculations .These three features are used parallel to get the better identification results, FAR is proved 0 with the three algorithms and FRR is 1 with the same i.e. SURF, HARRIS and MSER and matching the maximum ...

The classification of ultrasound scan images is important in monitoring the development prenatal and maternal structures. This paper proposes a big data system for Doppler that combines residual maximally stable extreme regions speeded up robust features (SURF) with decision tree classifier. algorithm first preprocesses before detecting extremal (MSER). A few essential are chosen from MSER regi...

Abstract Background Minimally invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation increasingly used in minimally (MIS), but current solutions require the use of reference markers surgical field for both patient and instruments tracking. Purpose To improve reliability facilitate clinical workflow, this study proposes a new marker-free tracking framework based...

The invariant feature detectors are essential components in many computer vision applications, such as tracking, simultaneous localization and mapping (SLAM), image search, machine vision, object recognition, 3D reconstruction from multiple images, augmented reality, stereo vision, and others. However, it is very challenging to detect high quality features while maintaining a low computational ...

Email: [email protected] [email protected] Abstract: Content-Based Image Retrieval (CBIR) has received an extensive attention from researchers due to the rapid growing and widespread of image databases. Despite the massive research efforts consumed for CBIR, the completely satisfactory results have not yet been attained. In this article, we offer a new CBIR technique that relies on extracting...

This paper investigates the coincidence between six interest point detection methods (SIFT, MSER, Harris-Laplace, SURF, FAST & Kadir-Brady Saliency) with two robust “bottom-up” models of visual saliency (Itti and Harel) as well as “task” salient surfaces derived from observer eye-tracking data. Comprehensive statistics for all detectors vs. saliency models are presented in the presence and abse...

Interest point approaches that extract local features from images are commonly used in human action recognition field. In this paper, a comparison study is performed in which different interest point approaches are used. Each approach is discussed with its advantages and drawbacks. Common keypoints extractor like scale invariant features transform (SIFT), speeded up robust features (SURF), etc....