# A Novel Hybrid Edge Detection and LBP Code-Based Robust Image Steganography Method
###### Abstract  
In digital image processing and steganography, images are often described using edges and local binary pattern (LBP) codes. By combining these two properties, a novel hybrid image steganography method of secret embedding is proposed in this paper. This method only employs edge pixels that influence how well the novel approach embeds data. To increase the quantity of computed edge pixels, several edge detectors are applied and hybridized using a logical OR operation. A morphological dilation procedure in the hybridized edge image is employed to this purpose. The least significant bits (LSB) and all LBP codes are calculated for edge pixels. Afterward, these LBP codes, LSBs, and secret bits using an exclusive-OR operation are merged. These resulting implanted bits are delivered to edge pixels' LSBs. The experimental results show that the suggested approach outperforms current strategies in terms of measuring perceptual transparency, such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSI). The embedding capacity per tempered pixel in the proposed approach is also substantial. Its embedding guidelines protect the privacy of implanted data. The entropy, correlation coefficient, cosine similarity, and pixel difference histogram data show that our proposed method is more resistant to various types of cyber-attacks. t 10 2023 1 <concept>  
law enforcement, intelligence, and counterintelligence agencies. Commonly used cover media are images, audio, video, text, DNA sequences, etc. In the field of steganography, images are the most famous form of cover media for frequently communicating flexible, redundant content over the internet. The method in the state of the art is to implant secrets in either image pixels [7; 8], transform coefficients of pixel values [9], or predict error space. In all cases, an embedding method, known as an encoder, implants the secrets within an image by modifying its pixel values. When the data embedment is complete, the media is termed a stego image. The stego image is then sent to the target destination. At the destination, a decoder extracts the secret from the stego image. Some decoders might be able to rebuild the cover media from the stego media without any help from the sender side. If the scheme can extract both the secret message and the cover, the method is called a reversible process. On the other hand, the irreversible schemes only extract the secrets [10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26]. Reconstruction of the cover image is not their concern. Though reversible processes hide fewer data, they are more challenging to implement [27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45]. However, in both cases, the performance of the schemes are measured by imperceptibility, security, capacity, robustness and embedding complexity, etc. For enhanced data security, a very rigorous technique is to implant bits into edge pixels only. Such a scheme first applies an edge detection algorithm to find the edge pixels of an image. The edge pixels are then used to create data bits. Though these schemes have a low embedding capacity, they are famous for security reasons. Our goal is to hide information within those edge pixels. We studied several edge detection-based schemes. However, these are irreversible schemes. That is why our second goal is to make a reversible method that is similar to those ones. [PERSON] et al. [7] proposed a hybrid edge-based image steganography scheme. They combined canny and fuzzy logic-based edge images utilizing the OR operator in their method, and secret bits were implanted using the least significant substitution technique. Within image pixels, they kept track of the edge status. As a result, this design has a low embedding capacity as well as poor visual quality. To solve the problem of [7], [PERSON] and [PERSON] [8] proposed block and hybrid edge-based image steganography methods.