A compression-based distance measure for texture

A Compression Based Distance Measure for Texture

The analysis of texture is an important subroutine in application areas as diverse as biology, medicine, robotics and forensic science. While the last three decades have seen extensive research in algorithms to measure texture similarity, almost all existing methods require the careful setting of many parameters. There are many problems associated with a surfeit of parameters, the most obvious ...

Supervised Texture Classification Using a Novel Compression-Based Similarity Measure

Supervised pixel-based texture classification is usually performed in the feature space. We propose to perform this task in (dis)similarity space by introducing a new compression-based (dis)similarity measure. The proposed measure utilizes two dimensional MPEG-1 encoder, which takes into consideration the spatial locality and connectivity of pixels in the images. The proposed formulation has be...

A Review on Similarity Distance Measure, Color, Texture Features Available For Content Based Image Retrieval

The explosive growth of digital libraries due to Web cameras, digital cameras, and mobile phones equipped with such devices is making the database management by human annotation an extremely tedious and clumsy task. Thus there exists a need for developing an efficient expert technique that can automatically search the desired image from the huge database. Content-based image retrieval (CBIR) is...

Revision of a fuzzy distance measure

Texture based DICOM Image Compression

Image processing is one of the most researched area these due to the flooding of the internet with an overload of images. The noble medicine industry is not left untouched. It has also suffered with an excess of patient record storage and maintenance. With the advent of automation of the industries in the world the medicine industry has sought to change and provide a more portable feel to it. L...