Multiple circular-harmonic-function correlation filter providing specified response to in-plane rotation

Optimal tradeoff circular harmonic function correlation filter methods providing controlled in-plane rotation response

Correlation methods are becoming increasingly attractive tools for image recognition and location. This renewed interest in correlation methods is spurred by the availability of high-speed image processors and the emergence of correlation filter designs that can optimize relevant figures of merit. In this paper, a new correlation filter design method is presented that allows one to optimally tradeoff among potentially conflicting correlation output performance criteria while achieving desired correlation peak value behavior in response to in-plane rotation of input images. Such controlled in-plane rotation response is useful in image analysis and pattern recognition applications where the sensor follows a pre-arranged trajectory while imaging an object. Since this new correlation filter design is based on circular harmonic function (CHF) theory, we refer to the resulting filters as optimal tradeoff circular harmonic function (OTCHF) filters. Underlying theory, OTCHF filter design method, and illustrative numerical results are presented.

Partial rotation-invariant pattern matching and face recognition with a joint transform correlator

We describe the circular-harmonic (CH) image CH(mr), which is based on CH components for rotationally invariant pattern recognition. CH components of the order m, derived from an image in polar coordinates, are used to form a two-dimensional space together with the radial variable r. Filtering the CH(mr) image leads to a reference image with some rotational invariance. For a narrow-pass filter we have a single CH component with full rotation invariance; for an all-pass filter we have the original image with no rotational invariance; for a low-pass filter we form a reference image containing multiple circular harmonics with partial rotation invariance. Results of numerical simulations and optical experiments with a joint transform correlator are given that illustrate partial-rotation-invariant recognition for human face images.

Circular harmonic filters for the recognition of marine microorganisms

We present an application of circular-harmonic filters (CHF's) for the recognition of planktonic microorganisms. CHF's discriminated both genera Acartia and Calanus. The symmetry of genus Acartia permitted discrimination to the species and sex levels, whereas the asymmetry of the genus Calanus permitted discrimination only to the generic level. The differences among organisms of different sex of the genus Calanus could not be detected by these particular CHF's. More research needs to be carried out with more complex CHF's to enhance their performance and to permit the implementation of an automated optodigital system to identify and count marine microorganisms.