Digital image processing method employing histogram peak detection
First Claim
1. In a method of processing a digital image by computer, including the steps of forming a gray-level histogram of the digital image, forming a peak detection function from the gray-level histogram, employing the peak detection function to detect peaks in the histogram, and employing the location of detected peaks to process the image, the improvement wherein said step of forming a peak detection function comprises the steps of:
- a. forming a cumulative distribution function from said gray-level histogram;
b. smoothing said cumulative distribution function with a sliding window average of size w to produce a smoothed cumulative distribution function; and
c. subtracting said smoothed cumulative distribution function from said cumulative distribution function to produce said peak detection function; and
wherein said step of employing the peak detection function to locate peaks in the histogram includes the steps of;
a. identifying positive to negative zero crossings of the peak detection function as the start of a detected histogram peak, andb. identifying a maximum following such a positive to negative zero crossing as the end of a detected histogram peak.
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Abstract
In many digital image processing methods, it is desirable to selectively apply digital image processing to identifiable structures in the image. For this purpose it is known to select gray level thresholds between structures based upon the location of corresponding peaks in the gray level histogram of the digital image. However, it is a problem to automatically detect the locations of peaks in the histogram and to select the gray level thresholds. The present invention provides a method for automatically detecting the peaks and selecting gray level thresholds for segmenting a digital image into distinguishable structures including the steps of detecting peaks in a gray level histogram of the digital image by applying smoothing and differencing operators to the gray level histogram to generate a peak detection function wherein positive to negative zero crossings of the peak detection function represent the start of a peak, and maxima following such a zero crossing represents the end of a peak.
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Citations
6 Claims
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1. In a method of processing a digital image by computer, including the steps of forming a gray-level histogram of the digital image, forming a peak detection function from the gray-level histogram, employing the peak detection function to detect peaks in the histogram, and employing the location of detected peaks to process the image, the improvement wherein said step of forming a peak detection function comprises the steps of:
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a. forming a cumulative distribution function from said gray-level histogram; b. smoothing said cumulative distribution function with a sliding window average of size w to produce a smoothed cumulative distribution function; and c. subtracting said smoothed cumulative distribution function from said cumulative distribution function to produce said peak detection function; and
wherein said step of employing the peak detection function to locate peaks in the histogram includes the steps of;a. identifying positive to negative zero crossings of the peak detection function as the start of a detected histogram peak, and b. identifying a maximum following such a positive to negative zero crossing as the end of a detected histogram peak. - View Dependent Claims (3, 4, 5, 6)
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2. In a method of processing a digital image by computer, including the steps of forming a gray-level histogram of the digital image, forming a peak detection function from the gray-level histogram, employing the peak detection function to detect peaks in the histogram, and employing the location of detected peaks to process the image, the improvement wherein said step of forming a peak detection function comprises the step of:
- convolving the histogram with a function qw (n) of the form;
space="preserve" listing-type="equation">q.sub.w (n)=d(n)*s.sub.w (n)where ##EQU5## where w is an adjustable parameter representing the size of an averaging window, and wherein said step of employing the peak detection function to loacate peaks in the histogram includes the steps of; a. identifying positive to negative zero crossings of the peak detection function is the start of a detected histogram peak, and b. identifying a maximum following such a positive to negative zero crossing as the end of a detected histogram peak.
- convolving the histogram with a function qw (n) of the form;
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