Abstract:
In modern technology, the easy way of weather process, analysis and forecast are
Satellite or Radar system. But the easiest way of weather process, analysing is processed
by a creating software with image processing. Researcher explores their thought about
weather information based on hardware. In this paper represents the several research
papers different concept combines together and proposed to a new exploration of weather
process for the new generation. In this paper used to image processing tool to create base
information of weather processing. The random cloud image is a valuable source of
information in weather forecasting and early prediction of different atmospheric
disturbances such as cyclone, typhoons, hurricanes, and storms etc. A Content-Based
Image Retrieval (CBIR) system has been developed using the grey scale as retrieval
features from the random image assortment. Image classification used image clustering
for pixel value group into clusters based on similarity. Cluster pixel values purposes at
searching for common characteristics without knowing the exact data types. Image
indexing is stored pixel data to an index which is created in this research. The Euclidean
distance metric is used to compute the similarity and non-similarity between the images.
Keywords: Image retrieval, Euclidean distance, Content-based image retrieval using
gray scale retrieval features, noise, image clustering, k-mean cluster algorithm, image
indexing, similarity and non-similarity computations.
