This paper addresses the challenge of enhancing image captioning in low-resource languages. While substantial progress has been made in image captioning, the focus has primarily been on high-resource languages such as English, leaving languages like Hindi and German with limited resources to improve their image captioning capabilities. To overcome this limitation, we propose a method that leverages English captions as input to improve the quality of the image captions in low-resource languages. Our method is evaluated on two representative datasets, namely Hindi Flickr-8k and Multi-30k German, which serve as benchmarks for low-resource languages. A baseline model trained without English captions is used for comparison. The proposed method achieves higher BLEU scores than the baseline model on both datasets, as demonstrated by our experimental results. Furthermore, our method can be extended to other low-resource languages.