Illumination Robust Feature Descriptor Based on Exact Order

Exact order based feature descriptor for illumination robust image matching

We present a novel method for a feature descriptor called an exact order based descriptor (EOD). The proposed method consists of three steps. First, to resolve ordering ambiguity for pixels of the same intensity, an exact order image is created by changing the discrete intensity into a k-dimensional continuous value. Second, exact order based features are generated globally and locally. Finally...

Rotationally and Illumination Invariant Descriptor based on Intensity Order

A New Illumination Invariant Feature Based on SIFT Descriptor in Color Space

The SIFT descriptor is one of the most widely used descriptors and Is very stable in regard to change in rotation, scale, affine, illumination, etc. However, because of the greater emphasis on its insensitivity to geometric changes, this descriptor is weak in various illuminations. This method is based on key points extracted from the image. If there are many such points, a lot of time will be ...

A novel illumination-robust local descriptor based on sparse linear regression

a r t i c l e i n f o a b s t r a c t Robust face recognition under uncontrolled illumination conditions is an important problem for real face recognition systems. In this paper, we introduce a novel illumination-robust local descriptor named Sparse Linear Regression Binary (SLRB) descriptor. The SLRB descriptor is a bit string by binarizing the sparse linear regression coefficients in a local ...

Robust Stereo Feature Descriptor for Visual Odometry

In this paper, we propose a simple way to utilize stereo camera data to improve feature descriptors. Computer vision algorithms that use a stereo camera require some calculations of 3D information. We leverage this pre-calculated information to improve feature descriptor algorithms. We use the 3D feature information to estimate the scale of each feature. This way, each feature descriptor will b...