Fast and accurate near-duplicate image elimination for visual sensor networks

Fast Convex Layers Algorithm for Near-Duplicate Image Detection

This paper builds on a novel, fast algorithm for generating the convex layers on grid points with linear time complexity. Convex layers are extracted from the binary image. The obtained convex hulls are characterized by the number of their vertices and used as representative image features. A computational geometric approach to near-duplicate image detection stems from these features. Similarit...

Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced using considering the focus measurement in the spatial domain. However, the multi-focus image ...

Hash Functions for Near Duplicate Image Retrieval

This paper proposes new hash functions for indexing local image descriptors. These functions are first applied and evaluated as a range neighbor algorithm. We show that it obtains similar results as several state of the art algorithms. In the context of near duplicate image retrieval, we integrated the proposed hash functions within a bag of words approach. Because most of the other methods use...

Coverage Quality in Visual Sensor Networks

Comparison of Near-Duplicate Image Matching

Near-duplicate image detection requires the matching of slightly altered images to the original and will assist in the detection of forged images. Much effort has been devoted to visual applications that require effective image signature and similarity metrics. This paper presents an attention based similarity measure in which only very weak assumptions are imposed on the nature of the features...