Optical hit-miss morphological transform

Optically computing the hit-miss transform for an automated cervical smear screening system

The hit-miss transform serves as a region-of-interest locator for cells from cervical smear images that show abnormal changes, which are indicative of malignancy, in their nuclei. An optical implementation of the hit-miss transform algorithm uses an analog spatial light modulator for gray-scale modulation at the filter plane of a 4f optical correlator. Gray-scale modulation at the filter plane improves correlator performance in comparison with a binary phase-only filter (BPOF) by reduction of the edge enhancement of kernels used in morphological detection of cancerous cervical cells. The hit-miss transform with a gray-scale amplitude and binary phase optical filter (GABPOF) for the hit filter and a BPOF for the miss filter shows a 47% reduction in total error versus the use of only BPOF filters to locate abnormal cells.

Logic-operated mathematical morphology and its optical implementation

A more powerful tool for binary image processing, i.e., logic-operated mathematical morphology (LOMM), is proposed. With LOMM the image and the structuring element (SE) are treated as binary logical variables, and the MULTIPLY between the image and the SE in correlation is replaced with 16 logical operations. A total of 12 LOMM operations are obtained. The optical implementation of LOMM is described. The application of LOMM and its experimental results are also presented.

Hit-or-miss representation of a pattern spectrum and its optical implementation

We demonstrate that a pattern spectrum can be decomposed into the union of hit-or-miss transforms with respect to a series of structure-element pairs. Moreover we use a Boolean-logic function to express the pattern spectrum and show that the Boolean-logic representation of a pattern spectrum is composed of hit-or-miss min terms. The optical implementation of a pattern spectrum is based on an incoherent optical correlator with a feedback operation.

One-step implementation of the optical hit-miss transform

A spatial-encoding scheme for the one-step implementation of the optical hit-miss transform (HMT) is presented. The rank-order HMT, which yields better performance in the presence of noise and clutter, can also be carried out by the use of this scheme. Numerical simulations and experimental results have proved the scheme to be feasible.

Nonlinear optical hit-miss transform for detection

Morphological processing involves nonlinear low-level image-processing operations that can be realized on optical processors. Amodified version of the hit-miss morphological transform is described for object detection. Simulation results and optical laboratory realizations are presented. Some of the simple filters required can be realized as ternary-phase-amplitude optical filters.

Optoelectronic hit/miss transform for screening cervical smear slides

An optoelectronic morphological processor for detecting regions of interest (abnormal cells) on a cervical smear slide using the hit/miss transform is presented. Computer simulation of the algorithm tested on 184 Papsmear images provided 95% detection and 5% false alarm. An optoelectronic implementation of the hit /miss transform is presented, along with preliminary experimental results.

Rank-order and morphological enhancement of image details with an optoelectronic processor

In all-optical processors, enhancement of image details is the result of high-pass filtering. We describe an optoelectronic processor in which detail enhancement results from the digitally calculated difference between an original input image and its low-pass filtered version. The low-pass filtering is realized through the rank-order median and the morphological opening and closing operations calculated by use of the optical convolver. It is shown that the normalized difference between the morphological white and black top hats enhances bright and dark image details analogously to the rank-order unsharp masking.

Morphological and wavelet transforms for object detection and image processing

We consider the problem of detecting multiple distorted objects in an input scene with clutter. The input scenes contain different types of background clutter and multiple objects in different classes, with different object aspect views, different object representations, hot/cold/bimodal/partial object variations, and high/low contrast object variations. Several new optical morphological operations for use in the above detection problem and in other general low-level image-processing applications are described, and several examples of their use are provided. For difficult detection problems in which high detection rates and low false-alarm rates are required we combine morphological operations and optical wavelet transforms to reduce clutter and improve object detection. The details of this set of filters and initial testresults are given. The most computationally demanding operations required in all cases are realizable on an optical correlator.

Parallel optical image processing with image-logic algebra and a polynomial approach

An interesting relationship between an optical parallel-processing single-instruction-multiple-data generic language, called image-logic algebra, and a polynomial approach for processing binary images by electronic computers is shown. Using only two basic operations of the ILA, one can reformulate a number of algorithms developed earlier in the polynomial approach into algorithms in the ILA environment. Thus a large number of new algorithms for parallel optical processing of binary images can be developed in the ILA environment that are fast and efficient.

Sidelobe elimination for generalized synthetic discriminant functions by a two-filter correlation and subsequent postprocessing of the intensity distributions

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.