Kalpana C. Jondhale

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K-Means algorithm is an unsupervised clustering algorithm that classifies the input data points into multiple classes based on their inherent distance from each other. Success of k-means color image segmentation depends on parameter k. If numbers of clusters are estimated correctly, k-means image segmentation can provide good results. This paper proposes a(More)
This paper presents improved technique for reversible data hiding. It is based on dividing the image into blocks, intensity histogram of each block is generated and shifting the histograms of each image block between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. The(More)
Content based image retrieval is an important research area in image processing, with a vast domain of applications like recognition systems i. e. face, finger, iris biometric etc. It retrieves the similar type of images from repository of images based on users query. To retrieve similar images, color, and texture or shape features need to be extracted from(More)
Face recognition (FR) is affected by various factors such as change in illumination, pose, expression, aging and various backgrounds. In this paper face recognition system based on DCT pyramid feature extraction is presented. We applied DCT pyramid on each face image to decompose it into approximation subband and reversed L-shape blocks. Then simple set of(More)
Image processings applications like in object tracking, medical imaging, satellite imaging, face recognition and segmentation requires image denoising as the preprocessing step. Problem with current image denoising methods are bluring and artifacts introduces after removal of noise from image. Current denoising methods are based on patches of image has well(More)
Automatic face recognition is an important problem, but age invariant face recognition is a major challenge. The face appearance of a person is subject to significant change due to age progression over time. In this paper, the discriminative model is proposed to match face images of a subject at different ages. To develop a discriminative model for age(More)
The patch-less Progressive Image Denoising(PID) is physical process of reducing the noise in image based on deterministic annealing i.e. temperature decreases from high to low so that shape of kernel changes according to it. The results of PID implementation are good and excellent for both natural and computer generated images i.e. artificial or synthetic(More)
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