An Approach for Extracting Viewpoint Patterns using Geometric Directions
Pavan Kumar K1, S.V.N Srinivasu2

1Pavan Kumar K, Research Scholar, Department of Computer Science & Engineering, Acharya Nagarjuna University, Guntur, India.

2S.V.N Srinivasu, Professor, Department of Computer Science & Engineering, Narasaraopeta Engineering college, Guntur, India.

Manuscript received on 10 December 2018 | Revised Manuscript received on 17 December 2018 | Manuscript Published on 30 December 2018 | PP: 263-267 | Volume-8 Issue- 2S December 2018 | Retrieval Number: BS2714128218/19©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: Vast improvement in technology significantly increases in the collection of images in a huge quantity. Most of the technologies like IoT, sensors, scanners, point of sales, internet, etc. are gathering the data in the form of images. Image processing researchers introduces many algorithms to process the images and tried to extract information from the images. Due to the drastic development in data mining research give you an idea about the way for extracting the value from the data which helps to improve the business and image database is not an exception for this. Many researchers are trying to present the algorithm in the image mining area for extracting the value from the image data databases. Recently Wynne Hsu, Jing Dai, and Mong Li Lee introduced new type of patterns called viewpoint patterns which exhibit the invariant relationship between the objects. But the algorithm suffers from costly operation of building the object table at every level. We design a new algorithm for extracting the viewpoint patterns which builds the object table only once and uses this information at every level and our algorithm is based on the relationship between the objects only.

Keywords: Image Mining, Viewpoint Patterns, Data Mining, Invariant Relationship.
Scope of the Article: Computer Science and Its Applications