ISSN(Online): 2320-9801 ISSN (Print): 2320-9798 International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 3, March 2015 Copyright to IJIRCCE 10.15680/ijircce.2015.0303038 1644 An Image Removal Using Local Tetra Patterns for Content Based Image Retrieval Manish K. Shriwas 1 , Prof. Vivek. R. Raut 2 P.G. Scholar, Department of Electronics and Telecommunication, Prof. Ram Meghe Institute of Technology and Research, Badnera, Amravati, Maharastra, India 1 Associate Professor, Department Electronics &Telecommunication Engineering, Prof. Ram Meghe Institute of Technology and Research, Badnera, Amravati, Maharastra, India 2 ABSTRACT: Content-based image retrieval is a technique of automatic retrieval of images from large database that perfectly matches the query image. For the large database, many of the research works had been undertaken in the past decade to design efficient image retrieval system. On many fields such as industry, education, biomedical and research the amount of image data that has to be stored, managed, searched and retrieved grows continuously. In this paper, we propose a new image retrieval technique for Content-based image retrieval (CBIR) using local tetra pattern (LTP). The local tetra pattern (LTP) and local binary pattern (LBP) determines the correlation on grey level difference between referenced pixel and its surrounding neighbours. The proposed technique encodes the relationship between the referenced pixel and its neighbours and by via first-order derivatives in vertical and horizontal directions. The proposed algorithm has been experienced on different real images and its performance is found to be somewhat acceptable when compared with performance of conventional technique of content based image retrieval. In terms of average precision and average recall we calculated the performance of proposed method.. KEYWORDS: Content Based Image Retrieval, Local Tetra Pattern (LTP), Local Binary Pattern (LBP), Precision and Recall. I. INTRODUCTION There is a need to develop a proficient technique for automatically retrieved the desired image from large database. To retrieve the images in database mostly two methods are common in practice, text based image retrieval and visual based i.e. content based image retrieval (CBIR).In text based image retrieval systems, images are characterized by text information such as keywords and captions. Many communities had retrieved the image using a text based data management system [DBMS] in 1970. In this technique, the user retrieved the images using keywords and images were stored in database with text annotation. Various techniques used in text retrieval are Bag of words approach, a technique where in Stop words can be removed, correction in spelling etc. In text base system different problems occur such as incorrect spelling, never complete the annotation, same thing can be said in different ways [1]. It is not possible to retrieved images more precisely in text based image retrieval system and in case of large database(hundreds of thousands) result became inaccurate. Figure 1 and figure 2 shows the result of images search on Google and Yahoo via text annotation Flower. The term CBIR describes the method of retrieving desired images from a huge database collection on the basis of characteristics (such as colour, texture and shape) that can be automatically retrieved from the images themselves. In this technique, image is retrieve based on similarity matched between the query image and database images and similarity is measures in terms of its color, texture and shape.[2] In the early 1990s, due to increasing the growth of digital images as a accurate result in the Internet and new digital image sensor technologies. Progress in image retrieval related to different domain such as industrial, scientific, educational, biomedical and other have grown rapidly. To retrieve the images more accurately the new technology was introduced called as Content Based Image Retrieval system.