Image Change Detection: Identifying Changes or Anomalies in an Image

This code utilizes convolutional neural networks (CNNs) autoencoders to identify changes or anomalies in an image. Unlike traditional methods, this approach is not limited by the position and orientation of the camera. Autoencoders compress image information and then reconstruct the original image to identify any changes. The code compares important image features extracted by autoencoders to a reference image in order to detect changes. Keypoint features are specific to certain locations, edges, corners, and blobs. Anomalies are feature patterns that deviate from normal patterns. This method can be combined with other sensors to detect anomalies, and it is less dependent on camera position and image perspectives compared to pixel-based image detection methods.

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