1. A method of detecting objects in an image, comprising the steps of: providing an image defined by an array of pixels, each pixel from said array having an original value indicative of intensity; providing a first mask defined by two spaced-apart strip regions wherein a target region is defined between said two strip regions; applying, at each said pixel, a best fit criteria to a portion of said image defined by said first mask for a plurality of orientations of said first mask wherein said pixel is located within said target region for each of said plurality of orientations, said best fit criteria normalizing a mean square error of pixel intensities contained by said two strip regions by a mean square error of pixel intensities of said target region to generate a least squares error estimate for each of said plurality of orientations, wherein a best fit is indicated by a smallest least squares error estimate; generating, at each said pixel, an anomaly image defined by anomaly image pixels in correspondence with said array of pixels, wherein each said anomaly image pixel has a value defined as a difference between (i) said original value associated with a corresponding one of said array of pixels, and (ii) said smallest least squares error estimate; convolving said anomaly image with a second mask of a selected size and shape wherein convolution values are generated across said anomaly image, said convolution values that are greater than a threshold value being indicative of the presence of an object of interest in a region of said anomaly image, wherein one of said anomaly image pixels associated with a greatest one of said convolution values in said region is defined as a centroid of the object of interest; determining outer edges associated with the object of interest wherein a segmented object is defined by said outer edges with all pixels within said outer edges being assigned the same value; determining geometric features of said segmented object; and comparing said geometric features of said segmented object with selected threshold features to determine if said geometric features correlate with said selected threshold features.