This article provides an overview of the advancements and challenges in image recognition technology that utilizes machine learning. Image recognition involves identifying and categorizing objects in images, with the main goal of accurately classifying these objects. The paper outlines essential processes in image recognition, such as data acquisition, preprocessing, feature extraction , and classifier design, highlighting the importance of feature extraction and selection for improving accuracy . The  Comparison of ML and DL techniques and Algorithms used in Image Recognition can be described in this article and Classification of Images by help of machine Learning can be depicted. The aim is to draw which process is most suitable for classifying detected objects. Furthermore, the research discusses the evolution of image recognition, particularly through the combination of ML and DL techniques. By examining the broad applications of ML in this field, the article aims to offer insights that can enhance the development of machine learning applications in image recognition, thereby improving the effectiveness of image processing technologies.