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.

中文翻译：

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使用 DNA 转录和翻译进行基于内容的图像检索

DNA携带着地球上几乎所有生物的遗传信息。遗传信息的流动是通过一系列转录和翻译反应发生的，在这些反应中，DNA 被转化为决定生物体表型的氨基酸序列。DNA 的这一特性已被用于所提出的 CBIR 技术，其中图像首先存储在 DNA 序列中，然后提取其相应的氨基酸序列，用于形成特征向量。这不仅确保了特征向量的维数减少，而且还保留了必要的信息。然后将这些特征向量作为输入提供给各种分类器以用于训练和测试目的。然后应用集成学习来提高算法的检索效率。所提出的算法是一种新颖的方法，它利用基于 DNA 的计算效率来提高图像检索分类器的效率。实验结果表明，所提出的方法比现有的最先进算法更有效。