What I would do is to first get rid of the grid lines, then analyze what's left for cracks. To determine the grid line location I would use drawline to manually locate the horizontal lines between the rows of tiles. Then do it again for the vertical grid lines. If the vertical gridlines are perfectly equally spaced, and you know how many tiles there are, you can just draw the leftmost and rightmost one and then locate the others by interpolation. Then use false and linspace to create a binary image (mask) with the location of the grid lines set to true. Then use imdilate to thicken the lines a little bit. Now use that mask with grid lines in it along with regionfill to in-paint the grid lines in the original image. Now you should have an image with only cracks in it and no grid lines between the tiles. Then it gets a bit tricky because some of your cracks are light on a dark background and others are dark on a light background. You might have to find each type individually and combine the two detections afterwards.
For finding cracks or ridges you might look at ridge finding algorithms, like a Hessian Filter, Frangi filter, or COSFIRE filter. There are some in the File Exchange. Look at algorithms used in ophthalmology or angiography because those types of images usually have crack-like features on backgrounds of varying intensity. Here are some links that may help:
In addition, you can search the Image Processing literature for relevant terms:
