Image steganography is one of the prominent technologies in data hiding standards. Its goal is to embed confidential data into images without causing perceptible changes in the original image. Higher embedding capacity is one of the important requirements today, but increasing the hiding capacity distorts the stego's visual quality making the system easily detectable to the eavesdropper. An appropriate embedding technique along with an efficient system may achieve a fair balance between embedding capacity and stego image imperceptibility, but it is challenging. In this article, we present a randomized embedding approach that improves the security and robustness of the system by hiding secrets in RGB images. Instead of using the original cover image, a 5-LSBs modified cover image is subjected to a hybrid edge detection technique by using the Fuzzy, Canny, and Prewitt filters to maximize the payload capacity. The suggested approach embeds data using edge pixels only to reduce visually detectable distortion. The message is randomly incorporated into the edge pixels of the blue channel's LSBs. The experiments showed that the method is sufficiently resilient against statistical attacks and provides an increased hiding capacity for concealing secrets in cover images without compromising the quality of the stego image. Furthermore, the outcomes demonstrated that the suggested algorithm outperformed other comparable strategies in every evaluation criterion.