Users needing is to store and index the image data and retrieved the image on feature vector derived by the user. Content Based Image Retrieval (CBIR) is search engine to retrieving the desired image automatically from the large image database having different categories. Retrieving the relevant images from the database by using feature vector is the challenging and important task. It is also need to retrieve the images from variety of the domain that is the application of CBIR that domains are medicine, crime prevention ,Biometrics, architecture, Fashion and publishing. This paper present the method developed to search and retrieve the similar image using bit plane image. Bit plane images are formed by using threshold and using bit plane slicing. Mean, standard deviation and third moment of row and column pixel distribution of bit plane image is used as a feature vector. We use simple Euclidean distance to compute the similarity measures of images for Content Based Image Retrieval application. The average precision and average recall of each image category and over all precision and recall is considered for the performance measure.
CBIR, Bit Plane , Precision, Recall, Mean, Standard Deviation, Moment.