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MAT LAB 2015 Projects

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Variable-Length Signature for Near-Duplicate Image Matching

Abstract:

We propose a variablelength signature for nearduplicate image matching in this paper. An image is represented by a signature, the length of which varies with respect to the number of patches in the image. A new visual descriptor, viz., probabilistic center-symmetric local binary pattern, is proposed to characterize the appearance of each image patch. Beyond each individual patch, the spatial relationships among the patches are captured. In order to compute the similarity between two images, we utilize the earth mover’s distance which is good at handling variablelength signatures. The proposed image signature is evaluated in two different applications, i.e., nearduplicate document image retrieval and nearduplicate natural image detection. The promising experimental results demonstrate the validity and effectiveness of the proposed variablelength signature.


Steganography Using Reversible Texture Synthesis


Robust Representation and Recognition of Facial Emotions Using Extreme Sparse Learning


R eversible Image Data Hiding with Contrast Enhancement


Revealing the Trace of High – Quality JPEG Compression through Quantization Noise Analysis


Pareto – Depth for Multiple – Query Image Retrieval


Multifocus Image Fusion Based on NSCT and Focused Area Detection


Image Super – Resolutio n Based on Structure – Modulated Sparse Representation


Image Denoising by Exploring External and Internal Correlations


Face Recognition across Non – Unifo rm Motion Blur, Illumination, and Pose


Face Recognition across Non – Unifo rm Motion Blur, Illumination, and Pose


Face Recognition across Non – Unifo rm Motion Blur, Illumination, and Pose


Combining Left and Right Palmprint Images for More Accurate Personal Identification


A Probabilistic Approach for Color Correction in Image Mosaicking Applications


A Probabilistic Approach for Color Correction in Image Mosaicking Applications


A No – Reference Texture Regularity Metric Based on Visual Saliency


A Feature – Enriched Completely Blind Image Quality Evaluator


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