Blob detection as Constraint satisfaction problem?
The constraint satisfaction problem (CSP) is NP-complete.  Identifying blobs is a question about graph connectivity which is in P.  Therefore, yes, the question you're asking reduces to CSP but this doesn't tell you anything useful: it just says that CSP is at least as hard as this problem but it might be harder.  (In fact, it is strictly harder if P$\neq$NP.)  Since your problem is in P, it is not (believed to be) NP-complete.

A related question is whether the problem can be expressed directly as a CSP without needing a reduction.

If a blob is any connected region then, in particular, any blob contains two adjacent pixels and any two adjacent pixels are part of a blob.  Therefore, if all you want to know is whether an image contains at least one blob, this is a constraint satisfaction problem.

However, if you want to identify a whole blob (e.g., output a list of all the pixels within some blob) or identify or count all the blobs, the problem is no longer a CSP.  The reason for this is that CSPs are not able to express connectivity conditions: there is no CSP in a finite constraint language that says "This graph is connected" because every instance of CSP is equivalent to a first-order formula and first-order logic can't tell the difference between connected and disconnected graphs.