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To identify and process an image using Python, we can use the following steps:

1. Import libraries: We need to import certain libraries such as OpenCV, Numpy, and Matplotlib to work with images.

2. Load the image: We can use the imread() function from the OpenCV library to load the image. We should specify the file path, and the function will return an image in the form of an array.

3. Pre-process the image: We can resize, crop or perform other pre-processing operations to prepare the image for further processing.

4. Identify the features: We can use various techniques, such as template matching, edge detection, or contour detection, to identify the features in the image.

5. Process the image: We can perform various operations such as filtering, smoothing or thresholding, to enhance or manipulate the features.

6. Display and save the output: We can use the imshow() function from Matplotlib library to display the image, and imwrite() function of OpenCV to save the image output.

This is a high-level overview of how we can identify and process an image using Python. The exact steps and libraries used will depend on the specific project requirements.