Hybrid Feature based Natural Scene Classification using Neural Network

In this paper a classification for natural images is proposed using hybrid features. The objective of this paper is to develop an image content based classifier, which can perform identity check of a natural image. Here we have extracted wavelet and color features from a captured natural image to classify out of three groups. The developed technique is able to classify translation and rotation invariant matching among natural images using feed forward back propagation neural network. The database contains several hundreds of natural images of three groups namely coast, Forest, Mountain for classification and found good classification rate. References Ajay Kumar Singh, Shamik Tiwari, and V P Shukla, "Wavelet based multiclass Image classification using neural network", International Journal of Computer Applications

[1]  Shamik Tiwari,et al.  Statistical Moments based Noise Classification using Feed Forward Back Propagation Neural Network , 2011 .

[2]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[3]  Takeo Kanade,et al.  Neural Network-Based Face Detection , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Jack Sklansky,et al.  Image Segmentation and Feature Extraction , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Björn Johansson,et al.  A Survey on : Contents Based Search in Image Databases , 2000 .

[6]  Ramin Zabih,et al.  Comparing images using color coherence vectors , 1997, MULTIMEDIA '96.

[7]  M. H. Deokate,et al.  An Algorithm for Image Compression Using 2 D Wavelet Transform , 2012 .

[8]  Robert Marti,et al.  Which is the best way to organize/classify images by content? , 2007, Image Vis. Comput..

[9]  Abdulkadir Sengür,et al.  Wavelet transform and adaptive neuro-fuzzy inference system for color texture classification , 2008, Expert Syst. Appl..

[10]  Michael Unser,et al.  Texture classification and segmentation using wavelet frames , 1995, IEEE Trans. Image Process..

[11]  A. Şengur.  COLOR TEXTURE CLASSIFICATION USING WAVELET TRANSFORM AND NEURAL NETWORK ENSEMBLES , 2009 .

[12]  I. Daubechies.  Orthonormal bases of compactly supported wavelets , 1988 .

[13]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[14]  Aleksandra Mojsilovic,et al.  On the Selection of an Optimal Wavelet Basis for Texture Characterization , 1998, ICIP.

[15]  Abdulkadir Sengür,et al.  Wavelet packet neural networks for texture classification , 2007, Expert Syst. Appl..

[16]  K. S. Thyagarajan,et al.  A maximum likelihood approach to texture classification using wavelet transform , 1994, Proceedings of 1st International Conference on Image Processing.

[17]  Paul Scheunders,et al.  Wavelet correlation signatures for color texture characterization , 1999, Pattern Recognit..

[18]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[19]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[20]  Jihoon Yang,et al.  Constructive Neural-Network Learning Algorithms for Pattern Classification , 2000 .

[21]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.