Improved Generic Object Retrieval In Large Scale Databases By SURF Descriptor
Journal Title: Journal of Information Systems and Telecommunication - Year 2017, Vol 5, Issue 2
Abstract
Normally, the-state-of-the-art methods in field of object retrieval for large databases are achieved by training process. We propose a novel large-scale generic object retrieval which only uses a single query image and training-free. Current object retrieval methods require a part of image database for training to construct the classifier. This training can be supervised or unsupervised and semi-supervised. In the proposed method, the query image can be a typical real image of the object. The object is constructed based on Speeded Up Robust Features (SURF) points acquired from the image. Information of relative positions, scale and orientation between SURF points are calculated and constructed into the object model. Dynamic programming is used to try all possible combinations of SURF points for query and datasets images. The ability to match partial affine transformed object images comes from the robustness of SURF points and the flexibility of the model. Occlusion is handled by specifying the probability of a missing SURF point in the model. Experimental results show that this matching technique is robust under partial occlusion and rotation. The properties and performance of the proposed method are demonstrated on the large databases. The obtained results illustrate that the proposed method improves the efficiency, speeds up recovery and reduces the storage space.
Authors and Affiliations
Hasan Farsi, Reza Nasiripour, Sajjad Mohammadzadeh
Keywords
Related Articles
- EP ID EP211844
- DOI -
- Views 96
- Downloads 0
A Linear Model for Energy-Aware Scheduling Problem Considering Interference in Real-time Wireless Sensor Networks
An important factor in increasing quality of service in real-time wireless networks is minimizing energy consumption, which contradicts with increasing message delivery rate because of associating a time deadline to each...
SIP Vulnerability Scan Framework
The purpose of this paper is to provide a framework for detecting vulnerabilities in SIP (Session Initiation Protocol) networks. We try to find weaknesses in SIP enabled entities that an attacker by exploiting them is ab...
Parameter Estimation in Hysteretic Systems Based on Adaptive Least-Squares
In this paper, various identification methods based on least-squares technique to estimate the unknown parameters of structural systems with hysteresis are investigated. The Bouc-Wen model is used to describe the behavio...
A Conflict Resolution Approach using Prioritization Strategy
In current air traffic control system and especially in free flight method, the resolution of conflicts between different aircrafts is a critical problem. In recent years, conflict detection and resolution problem has be...
Joint Source and Channel Analysis for Scalable Video Coding Using Vector Quantization over OFDM System
Conventional wireless video encoders employ variable-length entropy encoding and predictive coding to achieve high compression ratio but these techniques render the extremely sensitive encoded bit-stream to channel error...