Feature Extraction Methods using Image Processing Techniques
R.Sunitha1, B Sharmila2, K.Srinivasan3

1R.Sunitha, Research Scholar, Anna University, Chennai (Tamil Nadu), India.
2B. Sharmila, Professor, Department of EIE, Sri Ramakrishna Engineering College, Coimbatore (Tamil Nadu), India.
3K.Srinivasan, Professor and Head, Department of EIE, Sri Ramakrishna Engineering College, Coimbatore )Tamil Nadu), India.

Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 1-7 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6310048419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Feature extraction plays a major role in identification of the algae species and also for their classification. The species are identified based on the size, shape, colour and texture. In identification of algal species by biological methods there is more possibility of human error and uncertainty. The task needs more attention and focus. Biological techniques seem to be more expensive, highly time-consuming and tedious for achieving good performance while identifying the species. Identification of algal species at their comparative rank of a collection in a nomenclature and the application in different real time evaluation is a complex process. This has encouraged developing systems to automate the identification algal images. When compared with biological techniques or methods the image processing technique is cost effective and good performance is achieved in very short time. In an image various features such as size, shape, color and texture are taken into consideration. In current days there has been an immense curiosity in the proposing many image classification strategies with respect to texture fora wide range of sectors. This survey paper presents methodologies used in feature extraction using image processing
Keywords: Feature Extraction, Image Processing, Texture, Image Classification, Segmentation, Algae, Identification, Recognition, Computation, Convolution Neural Network.

Scope of the Article: Image Processing