Interest Point Detection based on Adaptive Ternary Coding

12/31/2018
by   Zhenwei Miao, et al.
0

In this paper, an adaptive pixel ternary coding mechanism is proposed and a contrast invariant and noise resistant interest point detector is developed on the basis of this mechanism. Every pixel in a local region is adaptively encoded into one of the three statuses: bright, uncertain and dark. The blob significance of the local region is measured by the spatial distribution of the bright and dark pixels. Interest points are extracted from this blob significance measurement. By labeling the statuses of ternary bright, uncertain, and dark, the proposed detector shows more robustness to image noise and quantization errors. Moreover, the adaptive strategy for the ternary cording, which relies on two thresholds that automatically converge to the median of the local region in measurement, enables this coding to be insensitive to the image local contrast. As a result, the proposed detector is invariant to illumination changes. The state-of-the-art results are achieved on the standard datasets, and also in the face recognition application.

READ FULL TEXT
research
05/10/2019

Illumination Normalization via Merging Locally Enhanced Textures for Robust Face Recognition

In order to improve the accuracy of face recognition under varying illum...
research
04/07/2020

Adaptive Multiscale Illumination-Invariant Feature Representation for Undersampled Face Recognition

This paper presents an novel illumination-invariant feature representati...
research
10/13/2020

A Scale and Rotational Invariant Key-point Detector based on Sparse Coding

Most popular hand-crafted key-point detectors such as Harris corner, SIF...
research
05/30/2022

Median Pixel Difference Convolutional Network for Robust Face Recognition

Face recognition is one of the most active tasks in computer vision and ...
research
02/07/2018

SCK: A sparse coding based key-point detector

All current popular hand-crafted key-point detectors such as Harris corn...
research
12/21/2021

Pixel-Stega: Generative Image Steganography Based on Autoregressive Models

In this letter, we explored generative image steganography based on auto...
research
08/15/2019

Beyond Cartesian Representations for Local Descriptors

The dominant approach for learning local patch descriptors relies on sma...

Please sign up or login with your details

Forgot password? Click here to reset