init - 初始化项目

doc/js_tutorials/js_imgproc/js_thresholding/js_thresholding.markdown

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+Image Thresholding {#tutorial_js_thresholding}
+==================
+
+Goal
+----
+
+-   In this tutorial, you will learn Simple thresholding, Adaptive thresholding, Otsu's thresholding
+    etc.
+-   You will learn these functions : **cv.threshold**, **cv.adaptiveThreshold** etc.
+
+Simple Thresholding
+-------------------
+
+Here, the matter is straight forward. If pixel value is greater than a threshold value, it is
+assigned one value (may be white), else it is assigned another value (may be black).
+
+We use the function: **cv.threshold (src, dst, thresh, maxval, type)**
+@param src    input array.
+@param dst    output array of the same size and type and the same number of channels as src.
+@param thresh threshold value.
+@param maxval maximum value to use with the cv.THRESH_BINARY and cv.THRESH_BINARY_INV thresholding types.
+@param type   thresholding type(see cv.ThresholdTypes).
+
+**thresholding type** - OpenCV provides different styles of thresholding and it is decided
+by the fourth parameter of the function. Different types are:
+
+-   cv.THRESH_BINARY
+-   cv.THRESH_BINARY_INV
+-   cv.THRESH_TRUNC
+-   cv.THRESH_TOZERO
+-   cv.THRESH_OTSU
+-   cv.THRESH_TRIANGLE
+
+@note Input image should be single channel only in case of cv.THRESH_OTSU or cv.THRESH_TRIANGLE flags
+
+Try it
+------
+
+\htmlonly
+<iframe src="../../js_thresholding_threshold.html" width="100%"
+        onload="this.style.height=this.contentDocument.body.scrollHeight +'px';">
+</iframe>
+\endhtmlonly
+
+Adaptive Thresholding
+---------------------
+
+In the previous section, we used a global value as threshold value. But it may not be good in all
+the conditions where image has different lighting conditions in different areas. In that case, we go
+for adaptive thresholding. In this, the algorithm calculate the threshold for a small regions of the
+image. So we get different thresholds for different regions of the same image and it gives us better
+results for images with varying illumination.
+
+We use the function: **cv.adaptiveThreshold (src, dst, maxValue, adaptiveMethod, thresholdType, blockSize, C)**
+@param src             source 8-bit single-channel image.
+@param dst             destination image of the same size and the same type as src.
+@param maxValue        non-zero value assigned to the pixels for which the condition is satisfied
+@param adaptiveMethod  adaptive thresholding algorithm to use.
+@param thresholdType   thresholding type that must be either cv.THRESH_BINARY or cv.THRESH_BINARY_INV.
+@param blockSize       size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on.
+@param C               constant subtracted from the mean or weighted mean (see the details below). Normally, it is positive but may be zero or negative as well.
+
+**adaptiveMethod** - It decides how thresholding value is calculated:
+    -   cv.ADAPTIVE_THRESH_MEAN_C
+    -   cv.ADAPTIVE_THRESH_GAUSSIAN_C
+
+Try it
+------
+
+\htmlonly
+<iframe src="../../js_thresholding_adaptiveThreshold.html" width="100%"
+        onload="this.style.height=this.contentDocument.body.scrollHeight +'px';">
+</iframe>
+\endhtmlonly