基于内容的图像检索方法是根据图像所包含的色彩、纹理、形状以及对象的空间关系等信息，通过建立图像的特征矢量，并将其作为图像的索引来进行图像检索的技术，其检索效果与图像特征矢量的编码方式以及具体的图像检索方法都有着很密切的关系。为了提高图像的检索效率，提出了一种基于交互式遗传算法的图像检索方法，该方法首先采用“变均分单元”法对图像进行分割，并对图像的特征信息加以汇总，形成图像的特征矢量；然后在此基础上，使用“螺旋式”的图像拆分方式通过对图像特征数据进行编码来生成图像染色体，并使它参与遗传算法中的各种遗传操作。在图像的检索过程中，该方法采用交互式遗传算法，首先对系统在每一步提供的候选图像集进行评价，然后利用非均匀遗传算子来从图像库中选出接近用户需求的图像。进一步的实验肯定了其在基于内容的图像检索过程中的有效性，与其他相关工作的比较结果说明，该方法具有简捷、高效的特点。

CBIR(Content-based image retrieval) is an image retrieval method that exploits the feature vector of the image as the retrieval index, which is based upon the content, including colors, textures, shapes and distributions of objects in the image etc. The implementation of the image feature vector and the searching process take a great influence upon the efficiency and result of the CBIR. In the paper, a prospective retrieval method based upon the CBIR and the IGA (Interactive Genetic Algorithm) are proposed. Firstly, each image in the collection is segmented into a constant number of sub-images, and the content in each sub-image is computed to make up the feature vector of the image. Then the feature vector of every image is reshuffled in a helix way, to produce the image chromosome, which is used in the following genetic operations. The image chromosome not only characterizes the image, but makes a difference among different parts in the image. During the image retrieval process, the user can employs the IGA to find the image he/she needss for by means of the interaction with the system. In order to promote the efficiency of the IGA, 'Non-uniform Inheriting Operator' is adopted in the genetic operations. Finally, experiments are made and the simplicity and efficiency of the method are discussed.