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Object detection and recognition are crucial elements of any high level image analysis system. Convolutional Neural Networks (CNNs) or ConvNets have been applied for recognizing the category of the principal entity in an image for several years. One major benefit of convolutional networks is the use of shared weights in the intermediate convolutional layers, which reduces the required memory size...
In this work, we propose a character segmentation system from ancient palm leaf manuscripts written in ancient Arya Ezhuthu(which was popularized as script to write Malayalam from 17th century). The automatic recognition of handwritten text from digital images of palm leaves dating back to 10th century BC. This can enable context based searching in large volumes of digital document. The subject about...
Many researches are going on in the field of optical character recognition (OCR) for the last few decades and a lot of articles have been published. Also a large number of OCR is available commercially. In this literature a review of the OCR history and the various techniques used for OCR development in the chronological order is being done.
Computed tomography image based Computer Aided Diagnosis (CAD) could be crucially important in supporting liver cancer diagnosis. An effective approach to realize a CAD system for this purpose is described in this work. The CAD system employs automatic tumor segmentation, texture feature extraction and characterization into malignant and benign tumors. A Region of Interest (ROI) cropped from the automatically...
An innovative approach based on local components called Optimal Random Image Component Selection is presented in this paper. Here, features are extracted from the Optimal Random Image Components by Gabor wavelets using greedy approach is proposed. These feature vectors are then down-sampled to some size which is then classified based on minimum distance measure. The design of Gabor filters for facial...
In this paper, a three tier strategy is suggested to recognize the hand-printed characters of Devanagari script. In primary and secondary stage classification, the structural properties of the script are exploited to avoid classification error. The results of all the three stages are reported on two classifiers i.e. MLP and SVM and the results achieved with the later are very good. The performance...
Face recognition and expression analysis is one of the most challenging research areas in the field of computer vision. Even though face exhibits different facial expressions, which can be instantly recognized by human eyes, it is very difficult for a computer to extract and use the information content from these expressions. In this paper we present a method to analyze facial expression by focusing...
This paper presents an algorithm for recognition and segmentation of natural features in unstructured environments. By providing a Bayesian solution for the density estimation problem, the algorithm needs significantly less training data than conventional techniques and is applicable to different environments. The algorithm is based on colour and wavelet convolution of image patches to model the information...
This paper presents the sensitivity analysis of a new technique for automated classification of human hand gestures based on Hu moments for robotics applications. It uses view-based approach for representation, and statistical technique for classification. This approach uses a cumulative image-difference technique where the time between the sequences of images is implicitly captured in the representation...
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