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Structural Analysis and Design of Foundations: A Comprehensive Handbook for S...
An object distortion based image quality similarity
1. Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Title: An Object-Distortion Based Image
Quality Similarity
Abstract—Image quality assessment (IQA) aims to devise perceptual models to
predict the image quality consistently with human subjective evaluation. The
representative metrics focus on measuring the image quality with low-level
features. In this letter, we assumed that the distortion in specific regions containing
semantically significant objects would be enhanced by HVSsignificantly.
According to this hypothesis, a novel IQA metric based on a commonly used
object-detecting feature, Speed Up RobustFeatures (SURF), was proposed. First, it
determined the interest points which represented significant objects through the
SURF features both on the reference image and distorted image. Then it computed
the multilevel SURF descriptors differences between the reference image and the
distorted one. Finally, all the difference results were combined with a suitable
pooling strategy. Comparing with other nine state-of-the-art IQA models on three
biggest IQA databases, SURF-SIM demonstrated its highly competitive prediction
accuracy especially on complicated applications and excellent robustness across
different distortion types.
2. Software & Hardware requirement:
1. Hardware requirement:
1. PC
2. RAM minimum 2GB
3. HDD minimum 100GB
2. Software requirement:
1. MATLAB 7.0
2. Signal processing toolbox
3. Image processing toolbox
4. Mathematical toolbox
PROJECT FLOW:
First Review:
Literature Survey
Paper Explanation
Design of Project
Project Enhancement explanation
Second Review:
Implementing 40% of Base Paper
Third Review
Implementing Remaining 60% of Base Paper with Future Enhancement
(Modification)
For More Details please contact
Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Mail: logicmindtech@gmail.com