Encrypted image retrieval is a promising technique, for achieving data confidentiality and searchability in the cloud-assisted Internet of Things (IoT) environment. However, most image retrieval solutions have low retrieval efficiency and may leak the values and orders of similarity scores to the cloud server. Hence, if a malicious server learns user background information through some improper means, then the malicious server can potentially infer user preferences and guess the most similar image content according to similarity scores. To solve the above challenges, a privacy-preserving threshold-based image retrieval scheme that improves the retrieval efficiency and prevents the cloud server from learning the values and orders of similarity scores is proposed in Privacy-Preserving Threshold-Based Image Retrieval in Cloud-Assisted Internet of Things (2021 IEEE) paper. This project is the implementation of the same.