This paper provides a new approach to recognize facial expressions. In this paper, facial expression recognition is based on appearance based features or we can say that low level features. We used two different approaches to categories the expression into seven different classes. These classifications based on Scale Invariant Feature Transform (SIFT) and Local Gabor Binary Filter (LGBP). First...

We present a mobile image matching application for Android mobile phone called Virtual Telescope to assist users in viewing distant buildings. The application automatically augments photo's field of view by retrieving replacement images and satellite images from the Internet. The application adopts content based image retrieval method and allow user two choices of feature descriptor, namely Sca...

In this paper, we present a mirror reflection invariant descriptor which is inspired from SIFT. While preserving tolerance to scale, rotation and even affine transformation, the proposed descriptor, MIFT, is also invariant to mirror reflection. We analyze the structure of MIFT and show how MIFT outperforms SIFT in the context of mirror reflection while performs as well as SIFT when there is no ...

Features from the Scale Invariant Feature Transformation (SIFT) are widely used for matching between spatially or temporally displaced images. Recently a topology on the SIFT features of a single image has been introduced where features of a similar semantics are close in this topology. We continue this work and present a technique to automatically detect groups of SIFT positions in a single im...

The SIFT framework has shown to be effective in the image classification context. In [4], we designed a Bag-of-Words approach based on an adaptation of this framework to time series classification. It relies on two steps: SIFT-based features are first extracted and quantized into words; histograms of occurrences of each word are then fed into a classifier. In this paper, we investigate techniqu...

Registration of optical and synthetic aperture radar (SAR) images is challenging because extracting located identically unique features on both are tricky. This paper proposes a novel SAR image registration method based relative total variation (RTV) scale-invariant feature transform (SIFT), named RTV-SIFT, to extract points the edges structures construct structural edge descriptors improve acc...

A new SAR image registration method was Proposed based on improved SIFT algorithm. Which adopted multi-core system platform was used to overcoming the problem of high complexity algorithm of SIFT algorithm; According to the characteristics of SAR image, first of all, the source SAR image was enhanced in airspace, and finish the parallel extraction of feature points with the improved SIFT algori...

This paper presents a query-by-example word spotting in handwritten Arabic documents, based on Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representation. First the interest points are automatically extracted from the images using SIFT detector, then, we use SIFT descriptor to represent eac...