Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100ms, we found a marker of real-world scene size, i.e. spatial ...

Problem statement: Noise identification is predominant in any digital image processing algorithms, which helps in identifying the filters to smooth the image for further processing. Approach: An Artificial Neural Network (ANN) based approach was proposed for noise identification. The suggested technique involved seclusion of the noise samples and extracts their statistical features, which was t...

iran has not yet gained the desired place in world date market, due to not considering the world standards in the processes of grading and packaging. machine vision and image processing are two of the new techniques that have found their places of application in agricultural industry. in this research, a solution has been introduced for classification of mozafati date introducing 5 different gr...

The paper aims to optimize practical applications for detection and face recognition using HaarLike classifiers in conjunction with a centroid algorithm to detect the gaze direction. For selecting method we have implemented principal components analysis (PCA), and for image resizing after detected we used the interpolation method. The proposed algorithm is tested by a database of its own and by...

In recent years there has been a growing trend of using neural networks for the development of intelligent systems that are able to simulate pattern recognition and object identification. Physical parameters of a coin are the sole criterion that is currently being used for Coin identification by machines. As physical features can easily be easily imitated another criterion which is not based on...

Handwriting recognition has been one of the most fascinating and challenging research areas in the field of image processing and pattern recognition in the recent year. Now a days the research work on handwriting recognition focusing toward evolving new techniques and methods that would reduce the processing time while maintaining higher recognition accuracy. A brief review of various Soft Comp...

Recurrent neural networks, as dynamical systems, are usually used as models for solving computationally intensive problems. Because of their inherent nature of parallel and distributed information processing, recurrent neural networks are promising computational models for real-time applications. Constrained optimization problems arise in a wide variety of scientific and engineering application...

in many autonomous mobile applications, robots must be capable of analyzing motion of moving objects in their environment. duringmovement of robot the quality of images is affected by quakes of camera which cause high errors in image processing outputs. in thispaper, we propose a novel method to effectively overcome this problem using neural networks and kalman filtering theory. thistechnique u...

This article presents PAPRICA-3, a high-speed 32-neurons slice for real-time neural processing of images. The system is a programmable parallel processor array with the instruction set tailored to the emulation of neural networks and to image processing. Dedicated hardware features allow simultaneous image acquisition, image processing and neural network emulation. The 32-neurons slice is casca...