ENHANCED MULTIQUERY SYSTEM USING KNN FOR CONTENT BASED IMAGE RETRIEVAL
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2017, Vol 16, Issue 1
Abstract
Content Based Image Retrieval (CBIR) techniques are becoming an essential requirement in the multimedia systems with the widespread use of internet, declining cost of storage devices and the exponential growth of un-annotated digital image information available in recent years. Therefore multi query systems have been used rather than a single query in order to bridge the semantic gaps and in order to understand user’s requirements. Moreover, query replacement algorithm has been used in the previous works in which user provides multiple images to the query image set referred as representative images. Feature vectors are extracted for each image in the representative image set and every image in the database. The centroid, Crep of the representative images is obtained by computing the mean of their feature vectors. Then every image in the representative image set is replaced with the same candidate image in the dataset one by one and new centroids are calculated for every replacement .The distance between each of the centroids resulting from the replacement and the representative image centroid Crep is calculated using Euclidean distance. The cumulative sum of these distances determines the similarity of the candidate image with the representative image set and is used for ranking the images. The smaller the distance, the similar will be the image with the representative image set. But it has some research gaps like it takes a lot of time to extract feature of each and every image from the database and compare our image with the database images and complexity as well as cost increases. So in our proposed work, the KNN algorithm is applied for classification of images in the database image set using the query images and the candidate images are reduced to images returned after classification mechanism which leads to decrease the execution time and reduce the number of iterations. Hence due to hybrid model of multi query and KNN, the effectiveness of image retrieval in CBIR system increases. The language used in this work is C /C++ with Open CV libraries and IDE is Visual studio 2015. The experimental results show that our method is more effective to improve the performance of the retrieval of images.
Authors and Affiliations
Meenu Meenu, Sonika Jindal
Tandem Communication Network Model with DBA having Non Homogeneous Poisson arrivals and Feedback for First Node
In this paper, we develop a two node tandem communication network model with dynamic bandwidth allocation and feedback for the first node. In most of the communication systems, the arrivals of packets follow Non-Homogene...
BIOMETRIC PERSONAL IDENTIFICATION ON 2D WAVELET TRANSFORM AND CHI-SQUARED MODEL
Iris recognition system consists of image acquisition, iris preprocessing, iris segmentation and feature extraction with comparism (matching) stages. The biometric based personal identification using iris requires accura...
Segmentation of Touching Hand written Telugu Characters by using Drop Fall Algorithm
Recognition of Indian language scripts is a challenging problem. Work for the development of complete OCR systems for Indian language scripts is still in infancy. Complete OCR systems have recently been developed for Dev...
INTELLECTUAL FREEDOM AND CENSORSHIP IN THE EYES OF NIGERIAN LAW
Intellectual freedom according to Article 19 of United Nations Universal Declaration of Human Rights is the right to freedom of thought and of expression of thought. Intellectual freedom guarantees everyone the right to...
Performance Analysis of Malicious nodes on Multi hop Cellular Networks
The existence of malicious nodes in multi hop cellular networks, which operate without a central administration infrastructure, can result in performance degradation or even disruption of the network operation. In this p...