Efficient Image Retrieval through Hybrid Feature Set and Neural Network

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Nitin Arora 1,2,* Alaknanda Ashok 3 Shamik Tiwari 2

1. Department of Computer Science & Engineering, Uttarakhand Technical University, Dehradun

2. School of Computer Science, Department of Informatics, University of Petroleum & Energy Studies, Dehradun

3. Department of Electrical Engineering, G. B. Pant University of Agriculture and Technology, Pant Nagar

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2019.01.05

Received: 18 Aug. 2018 / Revised: 6 Sep. 2018 / Accepted: 22 Sep. 2018 / Published: 8 Jan. 2019

Index Terms

Content-based Image Retrieval, Information Retrieval, Color features, Texture features, Shape features


Images are an important part of daily life. Any person cannot easily control the huge repository of digitally existing images. Extensive scanning of the image database is very much essential to search a particular image from the huge repository. In some cases, this procedure becomes very exhaustive also. As a result, if a count of ten thousand, lakhs or considerably more images are included in the image database, then it may be transformed into a tedious and never-ending process. Content-based image retrieval (CBIR) is a technique, which is used for retrieving an image. This type of image retrieval procedure is centered on the real content of the image. This paper proposed a model of the hybrid feature set of Haar wavelets and Gabor features and analyzed with different existing models image retrieval. Content-based image retrieval using hybrid feature set of Haar wavelets and Gabor features superiors on other models.

Cite This Paper

Nitin Arora, Alaknanda Ashok, Shamik Tiwari, "Efficient Image Retrieval through Hybrid Feature Set and Neural Network", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.1, pp. 44-53, 2019. DOI: 10.5815/ijigsp.2019.01.05


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