Text detection and recognition based on a lensless imaging system

Lensless cameras are characterized by several advantages (e.g., miniaturization, ease of manufacture, and low cost) as compared with conventional cameras. However, they have not been extensively employed due to their poor image clarity and low image resolution, especially for tasks that have high requirements on image quality and details such as text detection and text recognition. To address the problem, a framework of deep-learning-based pipeline structure was built to recognize text with three steps from raw data captured by employing lensless cameras. This pipeline structure consisted of the lensless imaging model U-Net, the text detection model connectionist text proposal network (CTPN), and the text recognition model convolutional recurrent neural network (CRNN). Compared with the method focusing only on image reconstruction, UNet in the pipeline was able to supplement the imaging details by enhancing factors related to character categories in the reconstruction process, so the textual information can be more effectively detected and recognized by CTPN and CRNN with fewer artifacts and high-clarity reconstructed lensless images. By performing experiments on datasets of different complexities, the applicability to text detection and recognition on lensless cameras was verified. This study reasonably demonstrates text detection and recognition tasks in the lensless camera system,and develops a basic method for novel applications

Histidine 90 function in 4chlorobenzoyl-coenzyme A dehalogenase catalysis

ABSTRACT: 4-Chlorobenzoyl-coenzyme A (4-CBA-CoA) dehalogenase catalyzes the hydrolytic dehalogenation of 4-CBA-CoA by attack of Asp145 on the C(4) of the substrate benzoyl ring to form a Meisenheimer intermediate (EMc), followed by expulsion of chloride ion to form an arylated enzyme intermediate (EAr) and, finally, ester hydrolysis in EAr to form 4-hydroxybenzoyl-CoA (4-HBA-CoA). This study examines the contribution of the active site His90 to catalysis of this reaction pathway. The His90 residue was replaced with glutamine by site-directed mutagenesis. X-ray crystallographic analysis of H90Q dehalogenase complexed with 4-HBA-CoA revealed that the positions of the catalytic groups are unchanged from those observed in the structure of the 4-HBA-CoA-wild-type dehalogenase complex. The one exception is the Gln90 side chain, which is rotated away from the position of the His90 side chain. The vacated His90 site is occupied by two water molecules. Kinetic techniques were used to evaluate ligand binding and catalytic turnover rates in the wild-type and H90Q mutant dehalogenases. The rate constants for 4-CBA-CoA (both 7 µM -1 s -1 ) and 4-HBA-CoA (33 and 11 µM -1 s -1 ) binding to the two dehalogenases are similar in value. For wild-type dehalogenase, the rate constant for a single turnover is 2.3 s -1 while that for multiple turnovers is 0.7 s -1 . For H90Q dehalogenase, these rate constants are 1.6 × 10 -2 and 2 × 10 -4 s -1 . The rate constants for EMc formation in wild-type and mutant dehalogenase are ∼200 s -1 while the rate constants for EAr formation are 40 and 0.3 s -1 , respectively. The rate constant for hydrolysis of EAr in wild-type dehalogenase is 20 s -1 and in the H90Q mutant, 0.13 s -1 . The 133-fold reduction in the rate of EAr formation in the mutant may be the result of active site hydration, while the 154-fold reduction in the rate EAr hydrolysis may be the result of lost general base catalysis. Substitution of the His90 with Gln also introduces a rate-limiting step which follows catalysis, and may involve renewing the catalytic site through a slow conformational change