Based on traditional bag of words model and combined with the features of human visual,
an improved image classification method is proposed in this paper. Firstly, compute the …

Bag-of-words is a classical method for image classification. The core problem is how to
count the frequency of the visual words and what visual words to select. In this paper, we …

Bag of words (BOW) model is widely applied in image classification. The traditional BOW
neglects the spatial information and object shape information, which fails to distinguish …

To overcome the disadvantages of general object recognition methods based on traditional
Bag of Words, this paper proposed a method for object recognition based on Region of …

Recently bag-of-words (BoW) model having been widely used in textual information
processing has been extended into many tasks in visual domain such as image …

Image classification is a method that distinguishes the different categories of targets based
on the different features of image. The current problem usually is that the feature modeling of …

Abstract The Bag-of-visual Words (BoW) image representation is a classical method applied
for various problems in the fields of multimedia and computer vision. During the process of …

The common method of image classification based on traditional SIFT local feature
description makes the description of the global information not comprehensive and has …

In this paper, we propose two ways of improving image classification based on bag-of-words
representation [25]. Two shortcomings of this representation are the loss of the spatial …

Abstract The Bag of Words (BoW) model is applied to object classification in this paper. An
optimized method based on the combination of Region Of Interest (ROI) extraction and …