A modern human being's health is determined by the amount of food consumed and the amount of calories contained in it, As a result, in order to maintain optimum health, one must monitor their calorie consumption. The body mass index indicates that you are overweight at a given point when it falls between 25 and 29. Assuming your BMI exceeds 30, you are obese. To grow in shape or maintain a stable weight, people must watch their calorie intake. The present calorie estimating system will be run manually. To quantify calories in a novel way, the suggested approach employs a deep learning system. Estimating dietary calories is critical in the medical industry. Because the goal of this food calorie estimation is to give good health conditions. This measurement is estimated using images of various foods, such as fruits and vegetables. The proposed CNN algorithm evaluates the food calorie value using an object recognition method as well as an image processing method known as image segmentation. Volume error estimation has been used as the primary component in the result, while calorie error estimation acts as the secondary factor. The volume estimation error eventually decreases by 20%. This shows that the proposed CNN model outperforms the previous model in terms of accuracy.