[특허]High order fractal feature extraction for classification of objects in images

High order fractal feature extraction for classification of objects in images 원문보기

IPC분류정보
국가/구분	United States(US) Patent 등록
국제특허분류(IPC7판)	G06K-009/62 G06K-009/36 G06K-009/46
출원번호	US-0629709 (1996-04-09)
발명자 / 주소	Nelson Susan R. Tuovila Susan M.
출원인 / 주소	The United States of America as represented by the Secretary of the Navy
대리인 / 주소	Gilbert
인용정보	피인용 횟수 : 43 인용 특허 : 0

초록 ▼

A method of identifying and classifying pre-detected target candidates in an image using pixel intensity and a fractalization process applied to the image. A raw analog image is digitized and normalized. The normalized pixel intensity content of the image is converted to fractal dimensions using a small and a large fractal box, sequentially. An array of special fractal features satisfying predetermined classification thresholds is prepared from the fractal dimensions for each box centered about each pre-detected target candidate in the image, thus classifying the detected objects as targets.

대표청구항 ▼

[ What we now claim as our invention is:] [1.] A method for discriminating objects such as targets from non-targets or background in a raw analog image which is pre-processed by being digitized and normalized and consisting of pixels, each of which having its intensity level valued between 0 and 255 where zero is black and 255 is white, and then subjected to a detector capable of identifying possible objects of interest based on appropriate characteristics such as size and brightness for further processing, and providing the x and y center coordinates of each such object in said image, said method having filenames, arrays, and parameters, and said method comprising the steps of:(a) initializing all filenames, arrays, and parameters;(b) inputting normalized image data of pixel intensities;(c) entering input variables consisting of the sizes of a large fractal box, a small fractal box and predetermined threshold test levels;(d) entering the x and y center coordinates of each object detected in said image in the fractal feature array;(e) calculating Sdim, the small box fractal dimension, Bdim, the big box fractal dimension and Fdif, the magnitude of the dimensional differences of Bdim and Sdim for each detected object center; and(f) subjecting said calculated fractal data for each detected object in each said image to classification thresholding where:(1) minimum thresholds for object acceptance using a counter TARGET1; and(2) thresholds for target classification using a counter TARGET.

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High order fractal feature extraction for classification of objects in images 원문보기

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High order fractal feature extraction for classification of objects in images 원문보기

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