Optical cellular continuous logic array for gray-scale image processing

Image distance transforms that use optical correlation

The image distance transform is a time-consuming global operation. We use optical correlation for the fast computation of binary image distance transforms. A joint transform correlator is proposed to implement the algorithm that accommodates the morphological threshold-decomposition concept. The proposed optical processor is programmable for computing Euclidean, city-block, and chessboard distance transforms in real time. Skeletonization by use of the distance transform and the rotation invariance of the Euclidean distance transform are demonstrated.

Parallel fuzzy inference with an optoelectronic H-tree architecture

Fuzzy inference is a method of reasoning with imprecise information. The mathematical operations of fuzzy inference can be stated in terms of generalized vector algebra, in which multiplication and summation are generalized to min and max operations. An optoelectronic H-tree architecture is ideally suited to perform these generalized vector operations in parallel and requires only a simple imaging optical interconnection. Appropriate data encodings and electronic circuitry permit large scale, pipelined systems.

Optical implementation of visible gray-image morphology with the visual-area-coding technique

We present a novel scheme of visible gray-image morphology with the visual-area-coding technique (VACT). The VACT is a technique of digitized analog-optical computing in which data are converted into visible coded patterns and processed with the visible form. Because the achievable operations in the VACT are identical to those of mathematical morphology, mathematical morphology is adapted to gray-image morphology with the VACT. Computer simulation and optical experiments of the several operations in mathematical morphology verify the correctness of the proposed technique. The processing capacity of the proposed method is estimated in terms of the space-bandwidth product.

Visual-area coding technique (VACT): optical parallel implementation of fuzzy logic and its visualization with the digital-halftoning process

A novel technique, the visual-area coding technique (VACT), for the optical implementation of fuzzy logic with the capability of visualization of the results is presented. This technique is based on the microfont method and is considered to be an instance of digitized analog optical computing. Huge amounts of data an be processed in fuzzy logic with the VACT. In addition, real-time visualization of the processed result can be accomplished.

Optically programmable two-channel sorting network based on a polarization- and area-encoded technique

We describe an optical cascadable polarization- and area-encoded sorting system that is capable of independently sorting two arrays of unipolar data, each in an arbitrary order specified by a corresponding instruction. The sorting instructions can be easily programmed by external optical signals. The system can be used for sorting a single array of bipolar data.