DNA Encoding-Based Nucleotide Pattern and Deep Features for Instance and Class-Based Image Retrieval.

Recently, DNA encoding has shown its potential to store the vital information of the image in the form of nucleotides, namely A, C, T , and G , with the entire sequence following run-length and GC-constraint. As a result, the encoded DNA planes contain unique nucleotide strings, giving more salient image information using less storage. In this paper, the advantages of DNA encoding have been inherited to uplift the retrieval accuracy of the content-based image retrieval (CBIR) system.

Content-Based Image Retrieval Using DNA Transcription and Translation.

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.