Vehicle Logo Recognition Using Image Matching and Textural Features

improvement of terrasar-x image matching using textural image features

nowadays, sar imaging systems have become more interesting for scientists. high spatial resolution of recent sar images has become a key factor for their accurate applications such as interferometry, radargrammetry and change detection. in these applications, sar image matching procedure is a critical step for conjugate point extraction which is much more difficult than the optical images. the ...

Using Global Features on Refined Image Parts for Logo Recognition

In this paper we address the problem of what parts of an image can be used to well perform content-based image retrieval system. Local parts are selected and refined based on the clustering of interest points obtained by Harris corners and minimum bounding box detectors. Global features such as invariant moments and color histograms of the extracted local regions are combined to find similar lo...

Image Colorization Using Discriminative Textural Features

This paper presents a novel approach to scribblebased image colorization. In the work reported here we have explored how to exploit the textural information to improve this process. For every scribbled image we extract the most discriminative features using linear discriminant analysis (LDA). After that, the whole image is projected onto a discriminative textural feature space. Our main contrib...

Fingerprint Image Segmentation Using Textural Features

Using negative shape features for logo similarity matching

A method for representing and matching logos based on positive and negative shape features is presented. Negative shape features represent an object that consists of several components enclosed in a simple geometric structure (e.g, a square) based on its interior with the components considered as holes. The goal is to find logos in a database that are most similar to a given sample logo. A bord...

Textural Features for Image Classification

Texture is one of the important characteristics used in identifying objects or regions of interest in an image, whether the image be a photomicrograph, an aerial photograph, or a satellite image. This paper describes some easily computable textural features based on graytone spatial dependancies, and illustrates their application in categoryidentification tasks of three different kinds of image...