Is grayscale conversion a necessary step in image preprocessing?

Question

I would like to know if image conversion to gray scale is required for all image preprocessing methods. I use a neural network for face recognition. Is it really necessary to convert it to a gray scale, or can I give color images also as input for neural networks?

Answer 1

Grayscale conversion is not required for image processing, but is usually performed for several reasons:

• Simplicity . Many image processing operations work on the plane of image data (for example, one color channel) at a time. Therefore, if you have an RGBA image, you may need to apply the operation on each of the four image planes, and then combine the results. Images with a gray scale contain only one image plane (containing gray scale intensity values).
• Data reduction . Suppose you have an RGBA (red-green-blue-alpha) image. If you convert this image to gray, you will need to process 1/4 of the data compared to the color image. For many image processing applications, especially for video processing (for example, tracking objects in real time), this data reduction allows the algorithm to work for a reasonable amount of time.

However, it is important to understand that while there are many benefits of converting to a gray scale, this is not always desirable. When you convert to gray scale, you not only reduce the amount of image data, but also lose information (such as color information). For many image processing applications, color is very important, and grayscale conversion may degrade results.

To summarize: If converting to grayscale still provides reasonable results for any application you are working on, this is probably desirable, especially because of the likely reduction in processing time. However, this is due to the release of data (color data), which can be very useful or required for many image processing applications.

Answer 2

No, this is not required, it simplifies things, so you often have to do it, but in general you can work directly with a color image in any representation (RGB, CMYK), simply using more dimensions (or more complex similarity / distance measurement / core) .