Modified
Image Segmentation Method based on Region Growing and Region Merging
Muthiah Mary1,
Lekshmi Padma2 and Maria John3
1Faculty of Electronics and Communication
Engineering, Noorul Islam University, India
2Department of Electrical and
Electrnics Engineering, Noorul Islam University, India
3Electrical and Electronics
Enhineering in St.Xavier’s Catholic College of Engineering, India
Abstract: Image
segmentation is one of the basic concepts widely used in each and every fields
of image processing. The entire process of the proposed work for image
segmentation comprises of 3 phases: Threshold generation with dynamic Modified
Region Growing phase (DMRG), texture feature generation phase and region
merging phase. by dynamically changing two thresholds, the given input image
can be performed as DMRG, in which the cuckoo search optimization algorithm
helps to optimize the two thresholds in modified region growing. after
obtaining the region growth segmented image, the edges are detected with edge
detection algorithm. In the second phase, the texture feature is extracted
using entropy based operation from the input image. In region merging phase,
the results obtained from the texture feature generation phase is combined with
the results of DMRG phase and similar regions are merged by using a distance
comparison between regions. The proposed work is implemented using Mat lab platform
with several medical images. the performance of the proposed work is evaluated
using the metrics sensitivity, specificity and accuracy. the results show that
this proposed work provides very good accuracy for the segmentation process in
images.
Keywords: DMRG, edge detection algorithm, cuckoo
search algorithm, texture generation, region merging.
Received September 10, 2014; accepted December
23, 2014