• K. Radhika
• P. Gopi
• S. Vamsi Krishna
• S. BandhavyaVardan

This paper involves image retrieval technique based on GLCM features. The aim of CBIR is to get accurate results with lower computational time. The content-based image retrieval has been employed in several application areas such as biomedicine, military, commerce, education, and web image classification and searching. Content-based Image Retrieval (CBIR) technology overcomes the defects of traditional text-based image retrieval technology, being appreciated for accuracy and efficiency. Intensity -Histogram is a simple method used to compare images with corresponding intensity values. The accuracy and efficiency is less if single feature (colour, texture, shape, etc.) is considered for extraction, to achieve the effective retrieval. To provide better accuracy, different features like colour, texture and shape are combined. SVM classifier is preferred for classification as it is producing accurate results. The features for classification are extracted using wavelet and LBP based feature extraction. Comparing state-of-art methods, the proposed method is at good accuracy and efficiency.

Content based image retrieval, GLCM, Histogram, SVM classifier, Classification

"Image Classification Using Wavelet and LBP based features for Image Retrieval Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.64-70, April-2019, Available :http://www.jetir.org/papers/JETIRBC06011.pdf

"Image Classification Using Wavelet and LBP based features for Image Retrieval Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp64-70, April-2019, Available at : http://www.jetir.org/papers/JETIRBC06011.pdf