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Image Segmentation divides a region into sub regions in such a way that the pixels in a sub region are similar. Satellite image segmentation, an application in image segmentation is to extract the patterns using image retrieval systems. Image Retrieval can be of a wide area in pattern recognition. Content-based can be of best form for retrieval of satellite images. Extraction of high-level features from the images in the form of query or keywords and reduces the semantic gap between the low-level features. To produce better accuracy, Relevance Feed-back based CBIR methods are used for reducing the semantic gap. The overall correlation between the taken satellite image and processed image is identified using Correlation Ratio. This paper focuses on the implementation of K-Means Clustering along with RF mechanism checks the similarity between original and extracted pattern

Pattern Extraction in Segmented Satellite Images By Reducing Semantic Gap Using Relevance Feedback Mechanism