Asit K. Datta

Arithmetic operations in optical computations using a modified trinary number system

A modified trinary number (MTN) system is proposed in which any binary number can be expressed with the help of trinary digits (1, 0, 1 ). Arithmetic operations can be performed in parallel without the need for carry and borrow steps when binary digits are converted to the MTN system. An optical implementation of the proposed scheme that uses spatial light modulators and color-coded light signals is described.

Analysis of pulse-fed power electronic circuits using Walsh function

A new operational method for the analysis of pulse–fed power electronic circuits is suggested, where input waveforms are expressed by a series combination of Walsh functions. The output response is obtained in terms of Walsh functions after operation by Walsh operational transfer function (WOTF). The current waveform of a DC chopper fed R-L load is approximated by piecewise constant solution and various average and r.m.s. currents of the same power electronic circuit are computed as an illustration.

Carry-less arithmetic operation of decimal numbers by signed digit substitution and its optical implementation

Abstract A new system of representing decimal numbers has been attempted where modified signed digit substitution rules are used to achieve arithmetic operations without carry/borrow and in parallel. Optical implementation of the suggested method is proposed.

Face Detection and Recognition: Theory and Practice

Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, drivers license issuance, law enforcement investigations, and physical access control. Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face detection and recognition systems currently in vogue. The book begins with an introduction to the state of the art, offering a general review of the available methods and an indication of future research using cognitive neurophysiology. The text then: Explores subspace methods for dimensionality reduction in face image processing, statistical methods applied to face detection, and intelligent face detection methods dominated by the use of artificial neural networks Covers face detection with colour and infrared face images, face detection in real time, face detection and recognition using set estimation theory, face recognition using evolutionary algorithms, and face recognition in frequency domain Discusses methods for the localization of face landmarks helpful in face recognition, methods of generating synthetic face images using set estimation theory, and databases of face images available for testing and training systems Features pictorial descriptions of every algorithm as well as downloadable source code (in MATLAB/PYTHON) and hardware implementation strategies with code examples Demonstrates how frequency domain correlation techniques can be used supplying exhaustive test results Face Detection and Recognition: Theory and Practice provides students, researchers, and practitioners with a single source for cutting-edge information on the major approaches, algorithms, and technologies used in automated face detection and recognition.

Signed-negabinary-arithmetic-based optical computing by use of a single liquid-crystal-display panel

Based on the negabinary number representation, parallel one-step arithmetic operations (that is, addition and subtraction), logical operations, and matrix-vector multiplication on data have been optically implemented, by use of a two-dimensional spatial-encoding technique. For addition and subtraction, one of the operands in decimal form is converted into the unsigned negabinary form, whereas the other decimal number is represented in the signed negabinary form. The result of operation is obtained in the mixed negabinary form and is converted back into decimal. Matrix-vector multiplication for unsigned negabinary numbers is achieved through the convolution technique. Both of the operands for logical operation are converted to their signed negabinary forms. All operations are implemented by use of a unique optical architecture. The use of a single liquid-crystal-display panel to spatially encode the input data, operational kernels, and decoding masks have simplified the architecture as well as reduced the cost and complexity.

Neural network trained morphological processing for the detection of defects in woven fabric

Basic morphological operations such as the erosion, dilation, opening, and closing often fail to detect various types of defects that may be present in woven fabric, mainly because of the heuristic selection of structuring element needed for these operations. In this paper, an artificial neural network (ANN) is utilized for the selection of structuring element, where ANN is trained by two pre‐assigned normalized numbers related to the warp and weft counts of the test fabric. The test gray fabric image is pre‐processed to remove noise and the interlaced grating structure of weft and warp and then converted to a binary image by thresholding. An intensity threshold value of the processed fabric image and the dimension of a sliding window needed for correlation operation are obtained from the trained ANN. Defects are detected after morphological reconstruction of the processed binary fabric image, where an ANN trained structuring element is used. The technique is tested on 317 samples for eight different types of defects in three types of plain woven fabrics from TILDA database and 92.8% success of detection is achieved.

New technique of arithmetic operation using the positional residue system

A simplified arithmetic digitwise positional operation is proposed that uses only moduli 2 and 5 of the residue number system.

A real-time optical parallel processor for binary addition with a carry

Abstract A bichannel optical shadow casting (OSC) technique has been proposed for logic operation and addition of multi-bit binary numbers. In case of addition the “carry” is accomodated by spatial placement of channels. Optoelectronic half and full adders, using spatial light modulators (SLM), optical to electrical converters, beam splitters and mirrors, form additional building blocks in the proposed processor, where operations are performed in parallel. Limitations are discussed.

A novel neural hetero-associative memory model for pattern recognition

A novel hetero-associative neural network model is proposed where the associative recall of pattern is achieved in a single pass through the system. Instead of forming the memory matrix by an outer product formulation, inner product cross-correlation of input data with each set of the library vector was performed. The limitation regarding the constraint imposed on the choice or selection of patterns that can be stored is avoided by such a formulation. The reliability of the proposed model is much improved in comparison to the heteroassociative memory models which uses outer product correlation formulation to construct the memory matrix.

Multi-input optical parallel logic processing with the shadow-casting technique

The lensless shadow-casting technique for coded pattern processing usually accommodates two inputs at a time to perform desired logical operations in parallel. A method of binary encoding is proposed that can accommodate multiple input patterns for simultaneous processing. With the proposed multiple-input encoding a carry-look-ahead technique of binary addition is developed that requires fewer processing steps than the conventional ripple-carry method. Experimental results for a few logic-processing operations are included to establish the validity of the proposed technique.