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Image understanding and analysis is the most exciting and fastest-growing research areas in the computer vision. Recent computer vision technologies and algorithms are support efficient semantic image analysis and retrieval. Image analysis is deal with image representation, estimation formula, and sampling density. Image analysis at semantic level is result in automatic extraction of image descriptions as per human perception which ultimately bridge semantic gap between low-level visual features and the high-level concepts capturing the conveyed meaning. Vital semantic image information is basically retrieved from image content, mainly from meaningful image objects and their mutual relations. In this paper, we present Semantic analysis of image by knowledge driven approach , start with Image content analysis with respect to semantic concepts, design image database and knowledge base on the basis of semantic content and retrieval, presentation and modification of image reference database or knowledge base for knowledge delivery intention. Experimental result shows improvement in image retrieval performance and accuracy.

This paper highlights content based image retrieval system using alignment of ontologies. The traditional contents-based image retrieval systems using single ontology retrieve imprecise images. To overcome this weakness, proposed image retrieval system designed using core semantic multiple ontology which merges feature ontology, semantic feature ontology, user ontology and metadata ontology. Proposed content based image retrieval system reduce semantic gap and provides highly accurate, efficient and effective image retrieval result.

Objective of our paper is to discuss latest pattern recognition applications, techniques and development. Pattern recognition has been demanding field from many years. We are also discuss driving force behind its swift development, that is pattern recognition is used to give human recognition intelligence acts as wheel of many techniques and applications in different fields. Pattern Recognition is recognition process which recognizes a pattern using a machine or computer. It is a study of ideas and algorithms that provide computers with a perceptual capability to put abstract objects, or patterns into categories in a simple and reliable way. The development and demand of pattern recognition technology is very fast and applications of pattern recognition are increase day by day. To fulfill this need, more and more researchers and scientists are evolved new pattern recognition techniques and apply them to many real life applications such as agriculture, robotics, biometrics, medical diagnosis, life form analysis, image processing, process control, information management systems, aerial photo interpretation, weather prediction, sensing of life on remote planets, behavior analysis, , Speech recognition, automatic diseases detection system in the infected plants, cancer detection system etc. with combination of other technology. Particular, in image retrieval system, pattern recognition play important for improving accuracy of image retrieval by using variety of recent techniques and their combination.

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