AN INTELLIGENT CULINARY INSTRUCTION GENERATOR FOR AUTOMATED RECIPE CREATION FROM VISUAL FOOD IMAGES

Abstract: Cooking is a creative and sensory process that relies heavily on the visual perception of food ingredients and their presentation. With recent advancements in Artificial Intelligence and Deep Learning, automated food recognition and recipe generation have become important research areas. This project presents a recipe generation system that utilizes Convolutional Neural Networks (CNNs) to analyze food images and automatically generate corresponding recipes. The proposed model accepts a food image as input and identifies the dish by extracting visual features through CNN-based image classification techniques. Based on the recognized food item, the system generates a complete recipe, including the dish name, required ingredients, and step-by-step cooking instructions. The developed approach aims to assist users in understanding and preparing food dishes from visual information alone, thereby enhancing cooking experiences and promoting intelligent food recommendation systems. Experimental results demonstrate the effectiveness of the proposed method in generating meaningful and relevant recipes from food images.