Open Access Journal

ISSN : 2394 - 6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

ISSN : 2394-6849 (Online)

Types of Segmentation A Comparative Study

Author : Dr. P. S. Ramaprabha 1 Naveena Preetha.M 2 Adithya.K.P 3

Date of Publication :7th July 2016

Abstract: Image segmentation has evolved into key areas of Image processing. This is largely due to its capability of ably assisting object identification and additionalscrutiny. The issue at hand is that there are a multitude of algorithms that venture to segment images in more sensible ways. But the bridging process to automatisation of object recognition is still at stake. So by a comparative study it would be facile to facilitate the better perception of the profound positive factors of each method. Some of the major techniques are taken for study and a profound inquiry is made on each of its intricacies. This will no doubt contribute valuable points that may impel the research further.

Reference :

  1. [1] R.Yogamangalam, B.Karthikeyan, “Segmentation techniques – comparison in Image processing”

    [2] W.T.M and B.S. Manjunathan, “ A framework of boundary detection & image segmentation”, IEEE trans. On image processing.

    [3] Caroline Pantofauru,Martial Herbert, “A comparison of Image segmentation algorithms”.

    [4]J.Jao&J.Zhang, G.Flemming, “A novel multiresolution colour image segmentation technique and its application to dermatoscopic image segmentation”.

    [5] Rotem, O.Greenspan, H.Goldberger, “Combining region and pattern recognition”

    [6] Sanka, Hlavac,Boyle, “Digital Image Processing and Computer vision”, Cengage Learning.

    [7] AmandeepKaur, Aayushi, “Image segmentation using watershed transform”, International journal of soft computing and Engineering.

    [8] Zoltan Kato, Ting – Chuen Pong, “A Markov Random field image segmentation for colour textured images”, Elsevier.


Recent Article