The increasing popularity of digital media and media editing software has led to widespread tampering with multimedia files for malicious purposes; law enforcement and forensics experts therefore require reliable and efficient means of detecting copy-move forgery. The most common form of tampering associated with digital images is copy-move forgery, in which a portion of an image is duplicated and another part of the same image is substituted in a different location. This paper proposes a blind forensics approach for the detection of copy-move forgery. The input image is segmented into overlapping blocks, whereupon a histogram of orientated gradients is applied to each block. Statistical features are extracted and reduced to facilitate the measurement of similarity. Finally, feature vectors are lexicographically sorted, and duplicated image blocks are detected by identifying similar block pairs after post-processing. Experimental results demonstrate that the proposed method is able to detect multiple examples of copy-move forgery and precisely locate the duplicated regions, even when dealing with images distorted by translation, rotation, blurring, adjustment of brightness, and color reduction.