Follow the link below and read the article, this will help you understand why CNN work better for image processing
https://towardsdatascience.com/convolutional-neural-networks-why-are-they-so-good-for-image-related-learning-2b202a25d757
1st answer is behind this article https://towardsdatascience.com/why-deep-learning-is-needed-over-traditional-machine-learning-1b6a99177063
2nd one - The main reason behind CNN is feature engineering not required. Before CNN, we need to spend so much time on feature selection ( algorithm for features extraction). When we compare handcrafted features with CNN, CNN performance well and it gives better accuracy. It is covering local and global features. It also learns different features from images.
In algorithm based image classification, we need to select the features(local, global) and classifiers. In some cases, global features worked well and in some cases, local features worked well.
Md. Rafiuzzaman Bhuiyan thank you but deep learning algorithm like RNN, LSTM also involve feature engineering. Why CNN is better than those especially for image ?
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