# A Watermarking Technique for Biomedical Images Using SMQT, Otsu, and Fuzzy C-Means
## 1 Introduction  
The ongoing advances in technology and computer networks have drawn a significant change in the biomedical sector. Currently, multimedia data are treated as a source for transmitting biomedical information such as patients' reports, hospital information, diagnoses, and so on. This transition encompasses patients, doctors, hospitals, and clinic centers [1]. Among the various types of multimedia data, biomedical images have an immense usage in the biomedical zone. Due to the easy use of the multimedia data, the biomedical images can be easily manipulated during transmission. This initiates huge security issues such as copyright and authentication because the biomedical data are highly confidential. The digital watermarking technique has captured great attention for restricting various illegal hazards and ensuring security. Biometric fingerprints and signatures have been used as the watermarks [2; 3]. Due to the sophistication of the medical images, digital watermarking has become more challenging. Although many research works focused on digital watermarking of medical images, there is no single model that adheres to all the security and privacy requirements. Therefore, it is crucial to develop watermarking models to fulfill all the required specifications.  
Digital watermarking is a technique of inserting any kind of additional data into the source image. The additional data is known as the watermark. The key feature of watermarking is informationhiding. Embedding sensitive data in the images facilitates data hiding and ensures maximum privacy. Watermarking medical images has two goals:  
1. Controlling reliability and authentication.
2. Hiding sensitive information of the patient.  
Moreover, watermarking procedures can be uniquely classified into three categories based on its function: validation, confidentiality, and a combination of both. During transmission, the image can be distorted due to illegal access, manipulation, and so on. As a result, the image quality is degraded while causing violation of authentication. Digital watermarking provides security as well as maintains the quality of the image. Watermarking ensures several properties of an image such as imperceptibility, robustness, and authentication [3]. Additionally, this process helps to identify the owner of that image.  
In this paper, an image watermarking model for protecting biomedical images is proposed. A watermark is embedded into the image using discrete wavelet transform (DWT) and extracted using inverse DWT (IDWT). The image security is ensured by comparing the original watermark before embedding and the extracted watermark after transmission. The following parameters are used to examine the performance of the proposed model: peak signal-to-noise ratio (PSNR), bit error rate (BER), cross correlation (CC), and structural similarity index measures (SSIM).  
The rest of this paper is organized as follows. Section 2 shows the literature study related to biomedical image watermarking. Section 3 illustrates the proposed model, which includes the pre-processing, segmentation, embedding, and extracting of the watermark using different algorithms. Section 4 presents the comparison between the proposed model and related models in terms of imperceptibility, robustness, and authentication. Finally, Section 5 concludes this paper.