Efficient Color and Texture Feature Extraction
Technique for Content Based Image Retrieval
System
Jayanthi Karuppusamy and Karthikeyan Marappan
Department of Electronics and Communication Engineering, Tamilnadu College of Engineering, India
Abstract: The future user needs in the field of multimedia
retrieval is the focus of many research and development activists. It is
empirically observed that no single algorithm is efficient in extracting all
different types of images like building images, flower images, car images and
so on. Hence, a thorough analysis of certain color, texture and shape
extraction techniques are carried out to identify an efficient Content Based
Image Retrieval (CBIR) technique which suits for a particular type of images.
The extraction of an image includes feature description, index generation and
feature detection. The low-level feature extraction techniques are proposed in
this paper are tested on Corel database, which contains 1000 images. The
feature vectors of the Query Image (QI) are compared with feature vectors of
the database images to obtain Matching Images (MI). This paper proposes Fuzzy
Color and Texture Histogram (FCTH), and Color and Edge Directivity Descriptor
(CEDD) techniques which extract the matching image based on the similarity of
color and edge of an image in the database. The Image Retrieval Precision value
(IRP) of the proposed techniques are calculated and compared with that of the
existing techniques. The algorithms used in this paper are Discrete Cosine
Transform (DCT), Discrete Wavelet Transform (DWT) and Fuzzy linking algorithm.
The proposed technique results in the improvement of the average precision
value. Also FCTH and CEDD are effective and efficient for image indexing and
image retrieval.
Keywords: CBIR, IRP, FCTH, CEDD.
Received January 11, 2014; accepted June 18, 2015