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Image (Meta)data Feature Extraction in Python
Exploring the metadata and color-related features of a photo image for further use in Analytics and ML
When working with image data, object recognition and its application have always been on top of mind for Data Analysts and Data Scientists. There has been very little focus on utilizing the metadata from these images. Truth is, we can get quite a lot of insights from the image metadata alone. In this article, I’ll be sharing how we can extract some prominent metadata-related features from an image (photo) file to further be processed and analyzed.
The complete code used in this analysis is shared under this Github project.
Understanding digital images
Computer stores digital image as an array, or a matrix, of square pixels (picture elements) arranged in columns and rows: in other words, a 2-dimensional matrix. Depending on how big or small these square pixels are, the image might appear more mosaic-like (pixelated) or smoother; which we refer to as image resolution.
These pixels contain information about color and intensity. For a grayscale image, the pixels don’t have color information but have intensity information in an 8-bit integer giving 256 possible different shades of…
