Image processing refers to the processing of images, which includes many different techniques that are used till we reach our goal. The processing output can either be in the form of an image, or a feature of the given image. This can be used for decision making and a more comprehensive image analysis. The Image compression process is a variation of data compression that is used on images without affecting their quality. Reduced size of the file makes sure that a lot of images can be put in a certain amount of memory / disk space. Processing also decreases the required time for the images to travel over the Internet or to be downloaded from different web pages. K - means clustering using Euclidean distance method includes vector quantization, which is originally a part of signal processing. It is very popular in cluster analysis for mining data. In this Project, we are using Image compression and segmentation algorithms using K – means clustering and Euclidean Distance method and many more algorithms used to process images.

The power system operational reliability depends on the proper functioning of transformers. The decreased quality of mineral oil deteriorates the insulation of the transformer results in the failure of the transformer. Thus, maintaining the quality of the mineral oil is a severe issue for power utilities. The major cause of mineral oil deterioration is the formation of oxidative products due to the over-temperature and overloading conditions. This research paper presents an artificial intelligence-based strategy for the reduction of oxidative products by regulating the temperature level accordingly. During the various critical operating conditions, the temperature sensor measures the temperature of mineral oil. The neural network is trained to recognise the various abnormal events according to increased temperature level.