Content-Based Image Retrieval using DNA Transcription and Translation.

Abstract

DNA carries the genetic information of almost all the living beings on the earth. The flow of genetic information takes place by a series of transcription and translation reactions in which the DNA gets converted into amino-acid sequences which determine the phenotype of an organism. This property of DNA has been used in the proposed CBIR technique in which the images are first stored in DNA sequences and then their corresponding amino-acid sequences are extracted which are used to form the feature-vectors. This not only ensures the reduction of the dimension of the feature-vectors but also the preservation of the necessary information. These feature-vectors are then given as input to various classifiers for training and testing purpose. Ensemble learning is then applied to enhance the retrieval efficiency of the algorithm. The proposed algorithm is a novel approach that uses the efficiency of DNA-based computing to increase the efficiency of classifiers for image retrieval. Experimental results show that the proposed method is more efficient than the existing state-of-the-art algorithms.