Repository: opencv
Issue: in opencv.js findTransformECC, argument inputMask is required (vs. documented optional) and does not seem to accept any input
Labels: category: javascript (js)

##### System information (version)
- OpenCV => 4.3.0 (opencv.js)
- Operating System / Platform => Windows 64 Bit
- Compiler => using Javascript

##### Detailed description

Using opencv.js (4.3.0 and tested todays build as well) findTransformECC  has 2 optional parameter (inputMask and gaussFiltSize) but if you don't include them you get an error that they are required. 

I have not found a way to represent ("inputMask=None") without getting an unhandled exception. "null" also does not work and a mask does not work.  

##### Steps to reproduce

    ```
function Align_img(){

            let image_baseline = cv.imread(imgElement_Baseline);
            let image = cv.imread('imageChangeup');

            let im1_gray = new cv.Mat();
            let im2_gray = new cv.Mat();
            let im2_aligned = new cv.Mat();

            //get size of baseline image
            width1 = image_baseline.cols;
            height1 = image_baseline.rows;

            //resize image to baseline image
            let dim1 = new cv.Size(width1, height1);
            cv.resize(image, image, dim1, cv.INTER_AREA);

            // Convert images to grayscale
            cv.cvtColor(image_baseline, im1_gray, cv.COLOR_BGR2GRAY);
            cv.cvtColor(image, im2_gray, cv.COLOR_BGR2GRAY);

            // Find size of image1
            let dsize = new cv.Size(image_baseline.rows, image_baseline.cols);

            // Define the motion model
            warp_mode = cv.MOTION_HOMOGRAPHY;

            // Define 3x3 matrix and initialize the matrix to identity
            let warp_matrix = cv.Mat.eye(3, 3, cv.CV_8U);

            // Specify the number of iterations.
            number_of_iterations = 5000;

            // Specify the threshold of the increment in the correlation coefficient between two iterations
            termination_eps = 0.0000000001; //1e-10;

            // Define termination criteria
            criteria = (cv.TERM_CRITERIA_EP | cv.TERM_CRITERIA_COUNT, number_of_iterations,  termination_eps);

            //Run the ECC algorithm. The results are stored in warp_matrix.
            cv.findTransformECC(im1_gray, im2_gray, warp_matrix, warp_mode, criteria, null, 1);

            // Use warpPerspective for Homography
            cv.warpPerspective (image, im2_aligned, warp_matrix, dsize, cv.INTER_LINEAR + cv.WARP_INVERSE_MAP);

            cv.imshow('imageChangeup', im2_aligned);

            im1_gray.delete();
            im2_gray.delete();
            im2_aligned.delete();

        };
    ```

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