Content Based Leaf Image Retrieval Using Feature Extraction Techniques

Kiruthiga Rajendran*
PG Scholar, Kongu Engineering College, Perundurai, India
Periodicity:January - March'2015
DOI : https://doi.org/10.26634/jdp.3.1.3286

Abstract

Content Based Image Retrieval technique is becoming increasingly important in various fields in order to store, manage and Retrieve images from database based on user query. Searching is done by image features such as texture, shape or different combinations of them. Texture feature plays an important role in image processing, computer vision and Pattern recognition. In this paper we propose a novel method of using dual tree complex wavelet transform for texture feature extraction followed by feature selection and similarity matching for retrieval of leaf images which matches the query image. Thus the performance is analyzed in terms of precision and recall values. This particular proposed method may find implementation in medical field of monitoring applications.

Keywords

CBIR, DT-CWT, Genetic Algorithm, Precision Call and Recall.

How to Cite this Article?

Rajendran,K. (2015). Content Based Leaf Image Retrieval Using Feature Extraction Techniques. i-manager’s Journal on Digital Signal Processing, 3(1), 17-21. https://doi.org/10.26634/jdp.3.1.3286

References

[1]. Waheeda Almayyan, Hala S. Own and Hussein Zedan (2010). “Iris Features Extraction Using Dual-Tree Complex Wavelet Transform”, International Conference of Soft Computing and Pattern Recognition, pp.18-22.
[2]. Jatindra Kumar Dash and Rahul Das Gupta (2012). “Content-Based Image Retrieval For Interstitial Lung Diseases”, IEEE conference.
[3]. Christina George Baby, D. Abraham Chandy (2013). “Content -Based Retinal Image Retrieval Using Dual-Tree Complex Wavelet Transform”,International Conference on Signal Processing, Image Processing and Pattern Recognition
[4]. Ghanshyam Raghuwanshi and Nishchol Mishra (2012). “Content based Image Retrieval using Implicit and Explicit Feedback with Interactive Genetic Algorithm”, International Journal of Computer Applications, Vol. 43, No.16.
[5]. Baddeti shyam and Yaravarappu Rao (2013). “An Effective Similarity measure via Genetic Algorithm for Content Based image Retrieval with Extensive Features”, The International Arab Journal of Information Technology, Vol.10 No.2.
[6]. Chih-Chin Lai and Ying-Chuan Chen (2011). “A User- Oriented image Retrieval System Based On Interactive Genetic Algorithm”, IEEE Transactions On Instrumentation And Measurement, Vol. 60, No. 10.
[7]. Shrikant Chavate and Vikas Gupta (2013). “An approach used for user Oriented Content Based Image Retrieval using Interactive Genetic Algorithm”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, No. 11, pp.-655-660.
[8]. Mohammed Behnam and Hossein Pourghassem (2013). “Feature Descriptor Optimization in Medical image Retrieval Based on Genetic Algorithm”, IEEE proceedings of th 20 Iranian conference on Biomedical Engineering, pp.285-289.
[9]. N. Anantrasirichai, J. Burn and David R. Bull (2014). “Robust Texture Features For Blurred Images Using Undecimated Dual-Tree Complex Wavelets”, IEEE Conference
[10]. Hill.P, Achim A and Bull D (2012). “The Undecimated Dual Tree Complex Wavelet Transform and its application to bivariate image denoising using a Cauchy model”, IEEE conference on Image processing.
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