Find all cycles in graph, redux

Question

I know there are a quite some answers existing on this question. However, I found none of them really bringing it to the point.
Some argue that a cycle is (almost) the same as a strongly connected components (s. Finding all cycles in a directed graph) , so one could use algorithms designed for that goal.
Some argue that finding a cycle can be done via DFS and checking for back-edges (s. boost graph documentation on file dependencies).

I now would like to have some suggestions on whether all cycles in a graph can be detected via DFS and checking for back-edges?
http://www.me.utexas.edu/~bard/IP/Handouts/cycles.pdf (found here on S.O.) states one methode based on cycle bases. Me personally, I don't find it very intuitive so I'm looking for a different solution.

EDIT: My initial opinion was apparently wrong. S. next answer by "Moron".
Initial opinion: My opinion is that it indeed could work that way as DFS-VISIT (s. pseudocode of DFS) freshly enters each node that was not yet visited. In that sense, each vertex exhibits a potential start of a cycle. Additionally, as DFS visits each edge once, each edge leading to the starting point of a cycle is also covered. Thus, by using DFS and back-edge checking it should indeed be possible to detect all cycles in a graph. Note that, if cycles with different numbers of participant nodes exist (e.g. triangles, rectangles etc.), additional work has to be done to discriminate the acutal "shape" of each cycle.

Answer 1

I have already answered this thoroughly, so check this:

Will a source-removal sort always return a maximal cycle?

The relevant part of the answer:

Perform a Depth-First Search on your graph.

You are interested in recognizing back edges, i.e., in the traversal, an edge which points back to an ancestor (in the DFS tree, which is induced by edges of visiting nodes for the first time) of the visited node. For example, if the DFS stack has nodes [A->B->C->D] and while you explore D you find an edge D->B, that's a back edge. Each back edge defines a cycle.

More importantly, the cycles induced by back-edges are a basic set of cycles of the graph. "A basic set of cycles": you can construct all cycles of the graph just by UNIONing and XORing cycles of the basic set. For example, consider the cycles [A1->A2->A3->A1] and [A2->B1->B2->B3->A2]. You can union them to the cycle: [A1->A2->B1->B2->B3->A2->A3->A1].