Background:
In the present digital world, Content Based Image Retrieval (CBIR) has gained significant
importance. In this context, the image processing technology has become the most sought one, as a result its demand has
increased to a large extend. The complex growth concerning computer technology offers a platform to apply the image
processing application. Well-known image retrieval techniques suitable for application zone are 1.Text Based Image
Retrieval (TBIR) 2. Content Based Image Retrieval (CBIR) and 3.Semantic Based Image Retrieval (SBIR) etc. In recent
past, many researchers have conducted extensive research in the field of content-based image retrieval (CBIR). However,
many related research studies on image retrieval and characterization have exemplified to be an immense issue and it should
be progressively developed in its techniques. Hence, by putting altogether the research conducted in the recent years, this
survey study makes a comprehensive attempt to review the state-of –the art in the field.
Aims:
This paper aims to retrieve similar images according to visual properties, which defined as Shape, color, Texture and
edge detection.
Objective:
To investigate the CBIR to achieve the task because of the essential and fundamentals problems. The present and
future trends are addressed to show come contributions and directions and it can inspire more research in the CBIR methods.
Result:
we present a deep analysis of the state of the art on CBIR methods; we explain the methods based on Color, Texture,
and shape, and edge detection with performance evaluation metrics. In addition, we have discussed some significant future
research directions reviewed.
Methods:
This paper has quickly anticipated the noteworthiness of CBIR and its related improvement, which incorporates
Edge Detection Techniques, Various sorts of Distance Metric (DM), Performance measurements and various kinds of
Datasets. This paper shows the conceivable outcomes to overcome the difficulties concerning re-positioning strategies with
an exceptional spotlight on the improvement of accuracy and execution.
Discussion:
At last, we have proposed another technique for consolidating different highlights in a CBIR framework that can give
preferred outcomes over the current strategies.
