IMAGE CLASSIFICATION WITH BAGS OF LOCAL FEATURES

Feature extraction is an important issue for generic image recognition. In recent years, methods based on the bag-of-keypoints technique have been quite successful and are widely used. However, this technique requires the quantization of local patches to build visual words as a preprocessing step, the computational cost of which is enormous. On the other hand, methods based on global image feat...

Image representation and classification are two fundamental tasks towards multimedia content retrieval and understanding. The idea that shape and texture information (e.g. edge or orientation) are the key features for visual representation is ingrained and dominated in current multimedia and computer vision communities. A number of low-level features have been proposed by computing local gradie...

Identiication of images irrespective of their location, size and orientation is one of the important tasks in pattern analysis. Use of global moment features has been one of the most popular techniques for this purpose. We present a simple and eeective method for gray-level image representation and identiication which utilizes fuzzy radial moments of image segments (local moments) as features a...

Facial reconstruction relies on the creativity of surgeons as well as a clear understanding in the properties of local flaps. Choosing the correct procedure begins with thorough analysis of the defect. Multiple reconstructive options often exist, which can then be narrowed and refined based on the specific qualities of the defect and the history of the patient. Careful planning ultimately leads...

Recently, the orderless Bag-of-Words (BoW) approach has proven extremely popular and successful in texture classification tasks [1, 2, 3]. Due to its impressive computational efficiency and good texture discriminative property, the BoW-based approach LBP [1] has gained considerable attention. In order to employ the advantages of the method of Zhang et al. [3] in combining complementary local fe...

LBP (Local Binary Pattern) as an image operator is used to extract LBPH (LBP histogram) features for texture description. In this paper, we present a novel method to use LBPH feature in ordinary binary classification problem. Given a restricted local patch, the Chi square distance between the extracted LBPH and a reference histogram is used as a measure of confidence belonging to the reference ...

Investigating a data set containing different sounds of several instruments suggests that local modelling may be a promising approach to take into account different timbre characteristics of different instruments. For this reason, some basic ideas towards a local modelling are realized in this report yielding a framework for further studies.

The aim of this paper is to present a study where we evaluate the optimal inclusion of the texture orientation in the classification process. In this paper the orientation for each pixel in the image is extracted using the partial derivatives of the Gaussian function and the main focus of our work is centred on the evaluation of the local dominant orientation (which is calculated by combining t...