With the rapid development of multimedia technology, considerable achievement has been achieved in image retrieval technology. On the one hand, users’ demand for cross-modal retrieval is increasing rapidly. On the other hand, deep hashing algorithms as one of the most prominent high-dimensional reduction methods have received extensive attention. Under such background, the cross-modal retrieval method based on deep hashing came into being. Although the cross-modal hashing learning method has moved a long way in recent years, it still has space of promotion. First, existing cross-modal based hashing algorithms can only map the feature vectors into binary codes with a fixed length. The length of hash codes cannot be modified according to the practical situation. Second, the saturation level of the probability function used in existing methods is too high to concentrate relevant samples very well, which results in low retrieval efficiency. To solve the above problem, a novel variable-length hash code based on adaptive weight was proposed in this paper. The length of hash codes could be adjusted according to the importance of each bit. And a novel probability function based on Cauchy distribution was proposed to generate compact binary codes and make hashing retrieval more efficient. The experiment shows that the proposed cross-modal image retrieval algorithm based on deep hashing outperforms existing related algorithms on the accuracy of retrieval.

随着多媒体技术的飞速发展，图像检索技术已经取得了可观的成就。一方面，用户对跨模式检索的需求正在迅速增长。另一方面，深度散列算法作为最重要的高维归约方法之一已受到广泛关注。在这种背景下，基于深度哈希的交叉模式检索方法应运而生。尽管跨模式哈希学习方法在最近几年已经发展了很长的路，但是它仍然有推广的空间。首先，现有的基于交叉模式的哈希算法只能将特征向量映射为具有固定长度的二进制代码。哈希码的长度不能根据实际情况进行修改。第二，现有方法中使用的概率函数的饱和度过高，无法很好地集中相关样本，从而导致检索效率低下。为了解决上述问题，提出了一种基于自适应权重的变长哈希码。哈希码的长度可以根据每个比特的重要性进行调整。提出了一种基于柯西分布的新概率函数，以生成紧凑的二进制代码，使哈希检索更加有效。实验表明，提出的基于深度哈希的跨模态图像检索算法在检索精度上优于现有的相关算法。提出了一种基于自适应权重的变长哈希码。哈希码的长度可以根据每个比特的重要性进行调整。提出了一种基于柯西分布的新概率函数，以生成紧凑的二进制代码，使哈希检索更加有效。实验表明，提出的基于深度哈希的跨模态图像检索算法在检索精度上优于现有的相关算法。提出了一种基于自适应权重的变长哈希码。哈希码的长度可以根据每个比特的重要性进行调整。提出了一种基于柯西分布的新概率函数，以生成紧凑的二进制代码，使哈希检索更加有效。实验表明，提出的基于深度哈希的跨模态图像检索算法在检索精度上优于现有的相关算法。