An Advanced Moving Object Detection Algorithm for Automatic Traffic Monitoring in Real-World Limited Bandwidth Networks ppt

Automated motion detection technology is an integral component of intelligent transportation systems, and is particularly essential for management of traffic and maintenance of traffic surveillance systems. Traffic surveillance systems using video communication over real-world networks with limited bandwidth often encounter difficulties due to network congestion and/or unstable bandwidth. This is especially problematic in wireless video […]

Self-Learning Based Image Decomposition with Applications to Single Image Denoising

  Abstract:           Decomposition of an image into multiple semantic components has been an effective research topic for various image processing applications such as image denoising, enhancement, and inpainting. In this paper, we present a novel self-learning based image decomposition framework. Based on the recent success of sparse representation, the proposed framework first learns an […]

Segmentation of Skin Lesions From Digital Images Using Joint Statistical Texture Distinctiveness

Abstract:-           Melanoma is the deadliest form of skin cancer. Incidence rates of melanoma have been increasing, especially among non-Hispanic white males and females, but survival rates are high if detected early. Due to the costs for dermatologists to screen every patient, there is a need for an automated system to assess a patient’s risk […]

On the Relation of Random Grid and Deterministic Visual Cryptography

Abstract:- Visual cryptography is a special type of secret sharing. Two models of visual cryptography have been independently studied: 1) deterministic visual cryptography, introduced by Naor and Shamir, and 2) random grid visual cryptography, introduced by Kafri and Kernel. In this paper, we show that there is a strict relation between these two models. In […]

Brain tumor detection using segmentation based Object labeling algorithm

 Abstract           In this paper, we propose an efficient brain tumor detection method, which can detect tumor and locate it in the brain MRI images. This method extracts the tumor by using K-means algorithm followed by Object labeling algorithm. Also, some preprocessing steps (median filtering and morphological operation) are used for tumor detection purpose. It is observed that the […]

Object Tracking via Robust Multitask Sparse Representation

  Abstract Sparse representation has been applied to the object tracking problem. Mining the self-similarities between particles via multitask learning can improve tracking performance. However, some particles may be different from others when they are sampled from a large region. Imposing all particles share the same structure may degrade the results. To overcome this problem, we propose a tracking algorithm based on […]

Attentional control of associative learning—A possible role of the central cholinergic system

ABSTRACT How does attention interact with learning? Kruschke [Kruschke, J.K. (2001). Toward a unified Model of Attention in Associative Learning. J. Math. Psychol. 45, 812–863.] proposed a model (EXIT) that captures Mackintosh’s [Mackintosh, N.J. (1975). A theory of attention: Variations in the associability of stimuli with reinforcement. Psychological Review, 82(4), 276–298.] framework for attentional modulation […]

Prostate MRI Segmentation Using Learned Semantic Knowledge and Graph Cuts

We propose a fully automated method for prostate segmentation using random forests (RFs) and graph cuts. A volume of interest (VOI) is automatically selected using supervoxel segmentation, and its subsequent classification using image features and RF classifiers. The VOIs probability map is generated using image and context features, and a second set of RF classifiers. […]

Diagnosis of ophthalmologic disorders in retinal fundus images a defective eye from a normal eye

Electrophysiological testing of patients with retinal disease began in clinical departments in the late nineteen forties. Under the influence of the Swedish pioneers, Holmgren (1865) and Granit (1933), the electroretinogram was being dissected into component parts and early intraretinal electrode studies were beginning to tell which cells or cell layers gave rise to the various […]

A Joint FED Watermarking System Using Spatial Fusion for Verifying the Security Issues of Teleradiology

ABSTRACT Teleradiology allows transmission of medical images for clinical data interpretation to provide improved e-health care access, delivery and standards. The remote transmission raises various ethical and legal issues like image retention, fraud, privacy, malpractice liability, etc. A joint FED watermarking system means joint fingerprint/encryption/dual watermarking system is proposed for addressing these issues. The system […]