A review of image features extraction techniques and their applications in image forensic

In these modern days, digital images become prominent information on the Internet and Social Media. The images can have a number of features with many secrets. To get these secrets, the information regarding the features of the images must be known. An image passes through the pre-processing stage before retrieving these features. For pre-processing, different operations such as normalization, thresholding, noise removal, etc. are applied to get the relevant features of the image. Feature extraction is the process of converting the input image into corresponding image features with the help of some algorithms such as the key point detector algorithm, edge detection algorithm, noise retrieval algorithm, etc. The objective of this survey article is to explore the latest methods for extracting image features and utilizing them in image forensics. These features are applied to detect the different types of image tampering attacks on the image with their detection techniques. Nowadays, the manipulation of an image is a very easy task with the help of different types of tools and software such as adobe photoshop, google picasa, and GNU’s Not Unix (GNU) Image Manipulation Program (GIMP), etc. To detect image tampering, features of the image play a very crucial role. A detailed review of different image features that are being utilized in image forensics has been done in the paper. The image features are colors, shape, texture, edges, noise, and key points. The different issues and challenges for detecting image tampering available with the existing techniques along with their performance have been presented in this paper. The future scope of the research work in the area of image processing has also been explored. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.