Kalpana C. Jondhale

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In this paper we developed Brain tumor techniques using tomography, such as MRI (Magnetic Resonance images) provide a plethora of pathophysiological tissue information that assists the clinician in diagnosis, therapy design/monitoring and surgery. Robust segmentation of brain tissues is a very important task in order to perform a number of computational(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)
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)
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)
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)
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)
  • Kapil Keshao Wankhade, Kalpana C. Jondhale, Vijaya R. Thool
  • Knowledge and Information Systems
  • 2017
Learning of rare class data is a challenging problem in field of classification process. A rare class or imbalanced class learning is the common problem faced by many real-world applications, because of this many researcher work focused on this issue. Rare class data always generate wrong results because of overwhelming accuracy of minority class by(More)