Various machine learning methods for writer independent recognition of Malayalam handwritten district names are discussed in this paper. Data collected from 56 different writers are used for the experiments. The proposed work can be used for the recognition of district in the address written in Malayalam. Different methods for Dimensionality reduction are discussed. Features consider for the re...

Face retrieval has received much attention in recent years. This paper comparatively studied five feature description methods for face representation, including Local Binary Pattern (LBP), Gabor feature, Gray Level Co-occurrence Matrices (GLCM), Pyramid Histogram of Oriented Gradient (PHOG) and Curvelet Transform (CT). The problem of large dimensionalities of the extracted features was addresse...

In this paper, we implemented an automated system for brain tumor detection, the main functionality of this system is divided in some parts are Segmentation, Object Labeling, HOG (Histogram Oriented Gradient), feature extraction and linear SVM implementation. For Segmentation we are using K-means algorithm, for Object Labeling HOG is use, HOG also use to extract texture feature, shape context f...

This project is an attempt to completely replace faces in video frames using Support Vector Machines (SVM) as classifiers on Histogram of Oriented Gradients (HOG). We trained an SVM classifier to first identify a face in an image using HOG descriptors and then identify fiducial markers like eyes, nose and mouth in the identified face using Matlab’s Cascade Object Descriptor. Once a convex hull ...

Automatic machine reading of texts in scenes is largely restricted by the poor character recognition accuracy. In this paper, we extend the Histogram of Oriented Gradient (HOG) and propose two new feature descriptors: Cooccurrence HOG (Co-HOG) and Convolutional Co-HOG (ConvCo-HOG) for accurate recognition of scene texts of different languages. Compared with HOG which counts orientation frequenc...

Despite the ubiquitous use of distance transforms in the shape analysis literature and the popularity of fast marching and fast sweeping methods—essentially HamiltonJacobi solvers, there is very little recent work leveraging the Hamilton-Jacobi to Schrödinger connection for representational and computational purposes. In this work, we exploit the linearity of the Schrödinger equation to (i) des...

Cervical cancer is one of the most common types of cancer in women worldwide. Most deaths of cervical cancer occur in less developed areas of the world. In this work, we introduce a new image dataset along with ground truth diagnosis for evaluating image-based cervical disease classification algorithms. We collect a large number of cervigram images from a database provided by the US National Ca...

To overcome the problem of occlusion in visual tracking, this paper proposes an occlusion-aware tracking algorithm. The proposed algorithm divides object into discrete image patches according to pixel distribution by means clustering. avoid drifting tracker false targets, extracts dominant features, such as color histogram or oriented gradient orientation, from these patches, and uses them cues...