scholarly journals Fuzzy based Multiple Dictionary Bag of Words for Image Classification

2012 ◽  
Vol 38 ◽  
pp. 2196-2206 ◽  
Author(s):  
K.S. Sujatha ◽  
P. Keerthana ◽  
S. Suga Priya ◽  
E. Kaavya ◽  
B. Vinod
Keyword(s):  
Image Classification ◽  
Bag Of Words

An Optimized Method for Image Classification Based on Bag of Words Model

2013 ◽  
Vol 34 (9) ◽  
pp. 2064-2070 ◽  
Author(s):  
Chun-hui Zhao ◽  
Ying Wang ◽  
KANEKO Masahide
Keyword(s):  
Image Classification ◽  
Bag Of Words

Discriminative Feature Selection in Image Classification and Retrieval

2012 ◽  
pp. 216-230
Author(s):  
Shang Liu ◽  
Xiao Bai
Keyword(s):  
Image Classification ◽  
Bag Of Words ◽  
Current Image ◽  
Visual Words ◽  
Discriminative Feature ◽  
Label Information ◽  
Novel Method ◽  
Category Knowledge ◽  
Supervised Image Classification ◽  
High Level

In this chapter, the authors present a new method to improve the performance of current bag-of-words based image classification process. After feature extraction, they introduce a pairwise image matching scheme to select the discriminative features. Only the label information from the training-sets is used to update the feature weights via an iterative matching processing. The selected features correspond to the foreground content of the images, and thus highlight the high level category knowledge of images. Visual words are constructed on these selected features. This novel method could be used as a refinement step for current image classification and retrieval process. The authors prove the efficiency of their method in three tasks: supervised image classification, semi-supervised image classification, and image retrieval.

scholarly journals Application of Analytics in Machine Vision using Big Data

2019 ◽  
Vol 7 (4) ◽  
Author(s):  
Noha Elfiky
Keyword(s):  
Big Data ◽  
Spatial Structure ◽  
Image Classification ◽  
Large Scale ◽  
Spatial Information ◽  
Image Representation ◽  
Structural Description ◽  
Bag Of Words ◽  
Spatial Image ◽  
3D Scene

The Bag-of-Words (BoW) approach has been successfully applied in the context of category-level image classification. To incorporate spatial image information in the BoW model, Spatial Pyramids (SPs) are used. However, spatial pyramids are rigid in nature and are based on pre-defined grid configurations. As a consequence, they often fail to coincide with the underlying spatial structure of images from different categories which may negatively affect the classification accuracy.The aim of the paper is to use the 3D scene geometry to steer the layout of spatial pyramids for category-level image classification (object recognition). The proposed approach provides an image representation by inferring the constituent geometrical parts of a scene. As a result, the image representation retains the descriptive spatial information to yield a structural description of the image. From large scale experiments on the Pascal VOC2007 and Caltech101, it can be derived that SPs which are obtained by the proposed Generic SPs outperforms the standard SPs.

scholarly journals Image classification by visual bag-of-words refinement and reduction

2016 ◽  
Vol 173 ◽  
pp. 373-384 ◽  
Author(s):  
Zhiwu Lu ◽  
Liwei Wang ◽  
Ji-Rong Wen
Keyword(s):  
Image Classification ◽  
Bag Of Words
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