Text Embedded into Encrypted Image based on Genetic Algorithm on Piece-Wise Linear Chaotic Map

Objective: To make texts and images secured by placing into. Method: Use of genetic algorithm for the selection of pixel's position in the plain images in which a class of fitness was used based on the intensity of the pixels influenced by neighbouring pixels. The algorithm presented in our previous work was secured and useful for text embedding where intensity of each pixel has an important role both in grey and colour images. Findings: Algorithms for text embedding into images have developed by a number of researchers. They simply placed the text into images sequentially and randomly. This has made text secured and difficult to retrieve but might not be impossible to retrieve. In the present paper, we proposed an added algorithm to Genetic Algorithm on Piece-Wise Linear Chaotic Map (PWLCM) for text embedding. This could have a double security on text encryption into images where images are itself encrypted. This made the diffusion processes more secured. Results and tests analysis are presented for comparison with existing text embedded algorithms in the literature. Applications: Public communication network, medical images are protected from forging, secret data and documents are to be safe from intruders.