Segmentation of Database Images Using Gradient Based Multiscale Morphological Reconstruction
A. Nithya, R. Kayalvizhi · International Journal of Electronics and Electical Engineering · 2015
The main purpose of this research is to improve the accuracy of object segmentation in database images by constructing an object segmentation algorithm. Image segmentation is a crucial step in the field of image processing and pattern recognition. Segmentation allows the identification of structures in an image which can be utilized for further processing. Both region-based and object-based segmentation are utilized for large-scale database images in a robust and principled manner. Gradient based MultiScalE Graylevel mOrphological recoNstructions (G-SEGON) is used for segmenting an image. SEGON roughly identifies the background and object regions in the image. This proposed method comprises of four phases namely pre-processing phase, object identification phase, object region segmentation phase, majority selection and refinement phase. After developing the grey level mesh the resultant image is converted into gradient and K-means clustering segmentation algorithm is used to segment the object from the gradient image. After implementation the accuracy of the proposed G-SEGON technique is compared with the existing method to prove its efficiency.