快速角点检测在MATLAB中的实现

Question

我试图在Matlab中实现快速角点检测算法，我知道已经有了一个预构建的版本。我不知道为什么我的实现似乎检测到那些甚至不接近边缘的特性，或者仅仅是糟糕的特性。

readImage1 = imread('img1.png');
im1 = rgb2gray(readImage1);
img1 = medfilt2(im1);

rowStart = 0.1 * size(img1, 1);
rowStart = fix(rowStart);
rowEnd = 0.9 * size(img1, 1);
rowEnd = fix(rowEnd);

colStart = 0.1 * size(img1, 2);
colStart = fix(colStart);
colEnd = 0.9 * size(img1, 2);
colEnd = fix(colEnd);

读我的照片，表演中位蓝色。我只想要特征检测从图像边缘开始一定的距离。

array = [ ; ];

for c = colStart:colEnd
    for r = rowStart:rowEnd

        %get the intesity of the pixel
        intensity = img1(r, c);

        temp = [r,c];

        intensity1 = img1((r+3), c);
        intensity5 = img1(r+1, c+3);
        intensity9 = img1(r-3, c);
        intensity13 = img1(r+1, c-3);

        threshold = 70;

        count = IntensityCount(intensity1, intensity9, intensity5, intensity13, intensity, threshold);

        if count >= 3
              array = [array; temp];
        end
    end
end

然后，对每个像素，将像素的强度与其4个最重要的邻居进行比较。如果检测到它为角，请将其保存到Nx2数组中。

之后，执行非最大抑制。

[rows, columns] = size(array);

discardArray = [ ; ];

for index = 2:rows
    currX = array(index);
    currY = array(index, 2);

    prevX = array(index - 1);
    prevY = array(index - 1, 2);

    if(adjacencyCheck(currX, currY, prevX, prevY))
        currScore = pixelScore(img1, currX, currY);
        prevScore = pixelScore(img1, prevX, prevY);

        if(currScore > prevScore)
            temp = [prevX, prevY];
            discardArray = [discardArray; temp];
        else
            temp = [currX, currY];
            discardArray = [discardArray; temp];
        end

    end
end

discardArray = unique(discardArray, 'rows');
finalArray = setdiff(array,discardArray, 'rows');

然后显示图像上的点。

[rows, columns] = size(finalArray);

for index = 1:rows
   img1 = insertMarker(img1, [finalArray(index), finalArray(index,2)], 'x'); 
end

imshow(img1);

用于强度检测和非最大抑制的函数。

function number = IntensityCount(int1, int9, int5, int13, origIntensity, thresh)

number = 0;

if abs(int1 - origIntensity) > thresh
    number = number + 1;
end

if abs(int9 - origIntensity) > thresh
    number = number + 1;
end

if abs(int5 - origIntensity) > thresh
    number = number + 1;
end

if abs(int13 - origIntensity) > thresh
    number = number + 1;
end

end

%Get the score by sum of absolute differences between the pixel and its neighbours.
function scoreNumber = pixelScore(img, r, c)

intOriginal = img(r,c);
intensity1 = img((r+3), c);
intensity3 = img(r+3, c-1);
intensity5 = img(r+1, c+3);
intensity7 = img(r-1, c+3);
intensity9 = img(r-3, c);
intensity11 = img(r-3, c-1);
intensity13 = img(r+1, c-3);
intensity15 = img(r-1, c-3);

scoreNumber = abs(intOriginal - intensity1) + abs(intOriginal - intensity3)+ abs(intOriginal - intensity5) + abs(intOriginal - intensity7) + abs(intOriginal - intensity9) + abs(intOriginal - intensity11) + abs(intOriginal - intensity13) + abs(intOriginal - intensity15); 
end

%Check pixel adjacency using Euclidean distance. 
function isAdjacent = adjacencyCheck(x1, y1, x2, y2)
xDist = x1 - x2;
yDist = y1 - y2;

dist = (xDist.^2 + yDist.^2).^0.5;

isAdjacent = dist <= 4;
end

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为什么我的算法会发现这么多不好的特征？

Answer 1

这是MATLAB语法中的一个不幸的困难，经常造成混淆。

如您所知，MATLAB将矩阵索引为[row,column]，这在线性代数中是自然的，完全适合于矩阵。但是由于MATLAB已经扩展到线性代数之外，所以通常使用矩阵来存储空间数据，其中x沿矩阵的列增加，y沿行增加。因此，应该反转一个空间位置[x,y]，以便在矩阵：[y,x]中找到索引。

insertMarker是一种函数，它以[x,y]的形式而不是索引的形式将空间位置取到矩阵中。因此，将[finalArray(index), finalArray(index,2)]切换到[finalArray(index,2), finalArray(index,1)]应该可以解决这个问题。

请注意，[finalArray(index,2), finalArray(index,1)]也可以编写为finalArray(index,[2,1])。