Image Type Water Meter Character Recognition Based on Embedded DSP

In the paper, we combined DSP processor with image processing algorithm and studied the method of water meter character recognition. We collected water meter image through camera at a fixed angle, and the projection method is used to recognize those digital images. The experiment results show that the method can recognize the meter characters accurately and artificial meter reading is replaced by automatic digital recognition, which improves working efficiency

1-(2,6-Difluoro­benzo­yl)-3-(2,3,5-tri­chloro­phen­yl)urea

The asymmetric unit of the title compound, C14H7Cl3F2N2O2, contains two unique molecules. The 2,3,5-trichloro­phenyl ring is almost coplanar with the urea group in both molecules, whereas the 2,6-difluoro­phenyl ring is twisted from the urea plane by 54.83 (10)° in one molecule and 60.58 (10)° in the other. An intra­molecular N—H—O hydrogen bond stabilizes the mol­ecular conformation. The crystal packing is formed by inter­molecular N—H—O hydrogen bonds and F⋯F inter­actions [2.841 (2) Å]

Robust Recovery of Subspace Structures by Low-Rank Representation

In this work we address the subspace recovery problem. Given a set of data samples (vectors) approximately drawn from a union of multiple subspaces, our goal is to segment the samples into their respective subspaces and correct the possible errors as well. To this end, we propose a novel method termed Low-Rank Representation (LRR), which seeks the lowest-rank representation among all the candidates that can represent the data samples as linear combinations of the bases in a given dictionary. It is shown that LRR well solves the subspace recovery problem: when the data is clean, we prove that LRR exactly captures the true subspace structures; for the data contaminated by outliers, we prove that under certain conditions LRR can exactly recover the row space of the original data and detect the outlier as well; for the data corrupted by arbitrary errors, LRR can also approximately recover the row space with theoretical guarantees. Since the subspace membership is provably determined by the row space, these further imply that LRR can perform robust subspace segmentation and error correction, in an efficient way.Comment: IEEE Trans. Pattern Analysis and Machine Intelligenc