Binary Image Analysis. YOU HAVE TO READ THE BOOK! reminder.

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Presentation transcript:

Binary Image Analysis

YOU HAVE TO READ THE BOOK! reminder

What is a binary image? An image that has two possible values for each pixel.

Thresholding A method that creates binary images. An operation that divides pixels into two groups: Foreground pixels and Background pixels

Thresholding A simple threshold has one value t. Usually: g=image>t; – Pixels with values greater than t are: foreground pixels. – Pixels with values smaller than t are: background pixels. How else can we do it?

Thresholding Threshold above and threshold below. How do we choose the threshold value? – Simple: mean or median. – Histogram. Adaptive thresholding. Multiband thresholding.

Thresholding 1.An initial threshold (T) is chosen, this can be done randomly or according to any other method desired. 2.The image is segmented into object and background pixels, creating two sets: – G 1 = {f(m,n):f(m,n)>T} (object pixels) – G 2 = {f(m,n):f(m,n)T} (background pixels) (note, f(m,n) is the value of the pixel located in the m th column, n th row) 3.The average of each set is computed. – m 1 = average value of G 1 – m 2 = average value of G 2 4.A new threshold is created that is the average of m 1 and m 2 – T’ = (m 1 + m 2 )/2 5.Go back to step two, now using the new threshold computed in step four, keep repeating until the new threshold matches the one before it (i.e. until convergence has been reached). Wikipedia (Thresholding)

Histogram Display of frequencies of pixel intensity values in an image. The number of pixels found for every intensity value. ram.htm

Multiband Thresholding shld.htm

Adaptive Thresholding Use different threshold values for different regions of the image.

Connected Components Labeling Used only with binary images. It groups objects in images. Scans the image for similar neighboring pixels.

Image Morphology Analysis and processing of geometrical structures. It is used in binary images. Operations performed by structuring elements on images. Erosion, Dilation, Opening, Closing

Image Morphology Structuring element example

Image Morphology Dilation

Image Morphology Erosion

Image Morphology Opening

Image Morphology Closing