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Near duplicate images are nothing but the similar images with minute change in the original image. These similar/transformed images are available in the internet and they are displayed as a result of user search. Discovery of these near duplicate images may permit the users to abstain from encountering the presentation of a similar picture in the result set. In this work, a detection methodology is presented to identify near duplicate image from the image set for an inquiry image by the user. Initially features are extracted from the images using Pulse-Coupled Neural Network. Once the features are extracted, similarity measure is calculated. Here Hellinger coefficient is computed. In view of the relationship between the inquiry image and the images in the image set, the near duplicate images are recognized. This results in effective detection of near duplicate images. The detected near duplicate images help the users to avoid redundancy in images, detect copyright infringement, illegal copy of images detection, facilitates users’ browsing since image search engine returns multiple copies of image for a particular query.