An Efficient Salient Feature Extraction by Using Saliency Map Detection with Modified K-Means Clustering Technique

Human eye is perceptually more sensitive to certain colors and intensities and objects with such features are considered more salient. Detection of Salient image regions is useful in applications such as object based image retrieval, adaptive content delivery, adaptive region-of interest based image compression, and smart image resizing .This problem can be handled by mapping the pixels into various feature spaces. This paper proposed a methodology that encapsulate K-Means Clustering with Saliency map detection technique to determine salient region in images using low-level features of luminance and color and then extract the features. Proposed methodology is simple to implement, computationally efficient and generates high quality saliency maps and saliency object of the same size and resolution as the input image. Here presented scheme identify salient regions as those regions of an image that are visually more conspicuous by virtue of their contrast with respect to surrounding regions.