This paper presents a novel object recognition method, of a mobile robot, by combining scale invariant feature transform (SIFT) and de-speckle filtering to enhance the recognition capability. The main idea of the proposed algorithm is to use SIFT programming to identify other robots after de-speckle filtering process to remove outside noise. Since a number of features are much larger than neede...

9 ABSTRACT: Aiming at long registration time and mismatch problems resulted by images that exist local region similar or generated SIFT vector similar in the traditional SIFT registration method, a fine registration method based on geometric constraints of block and parallel architecture is put forward. This method using SIFT algorithm parallelly extract feature points to calculate initial tran...

Traditional trademark image retrieval algorithm only using global feature easily makes mistaken retrieval, and scale invariant feature transform (SIFT) features have limited descriptive ability for image contour and high algorithm complexity. This paper proposes a trademark retrieval algorithm combining the image global features and local features. In this paper, we will firstly, extract Zernik...

Briefly, what approach or combination of approaches did you test in each of your submitted runs? • all runs: video decoding using ffmpeg library, sampling every 25th frame. • F_X_NO_TNO-ANNMSK_1: standard SIFT key point detection, exhaustive search using FLANN matching with query key points inside query mask. • F_X_NO_TNO-ANNMSK_3: standard SIFT key point detection, exhaustive search using FLAN...

This paper proposes an efficient three fold stratified SIFT matching for iris recognition. The objective is to filter wrongly paired conventional SIFT matches. In Strata I, the keypoints from gallery and probe iris images are paired using traditional SIFT approach. Due to high image similarity at different regions of iris there may be some impairments. These are detected and filtered by finding...

Template matching is a technique widely used for finding patterns in digital images. An efficient template matching algorithm should be able to detect template instances that have undergone geometric transformations. Similarly, a color template matching should be able to deal with color constancy problem. Recently we have proposed a new grayscale template matching algorithm named Ciratefi, inva...

Here we present performance evaluation of different routing protocols such as SIFT, GPSR and GOSR using different mobility models like Fluid Traffic Model (FTM), Intelligent Driver Model and Random Waypoint Model (RWM) with Intersection Management (IDM-IM). We present simulation results that demonstrate the importance of choosing a mobility model in the simulation of a Vehicular Network Protoco...

In order to ensure that SAR scene matching aided navigation system can acquire the position errors and yawing errors simultaneously, we propose an image matching algorithm based on Scale Invariant Feature Transform (SIFT). However, the SIFT is proposed for optical image, and its performance degrades when used in SAR image. To enhance the adaptability of SIFT, two ways are employed. One is the a...

Image matching is a key part of many remote sensing image processing and image analysis. The traditional gray correlation matching algorithm based on corner point because they do not have the rotational invariance requires manual intervention to roughly match can not be automated. SIFT (Scale invariant feature transform) algorithm to solve the image rotation, scaling and other issues, but for t...

The Sorting Intolerant from Tolerant (SIFT) algorithm predicts the effect of coding variants on protein function. It was first introduced in 2001, with a corresponding website that provides users with predictions on their variants. Since its release, SIFT has become one of the standard tools for characterizing missense variation. We have updated SIFT's genome-wide prediction tool since our last...