## 1 Introduction  
The high-volume production of flexible electronics using roll-to-roll (R2R) manufacturing technologies is a promising upscaling solution for the organic electronics industry [1; 2; 3; 4]. R2R printing enables cost-efficient industrial production of optoelectronic devices, such as organic and polymer solar cells (OPVs) and organic light emitting diodes (OLEDs) [5; 6; 7; 8]. Since electronic devices have a multilayered structure, local defects within the thin layers may cause severe malfunctions of the entire module. During the processing of the individual layers, functionality tests are required to visualize and control the quality of each layer [8].  
Early-stage defect detection can improve the production yield and reduce the amount of waste, as the defected parts will not be used for further processing. It is also easier to recycle the non-functional material before printing any other layers on top of it. The EC-funded OLEDSOLAR Project [9; 10] aims to develop innovative manufacturing processes and in-line monitoring techniques to detect defects in solar panels. This study, forms part of the OLEDSOLAR project which, in-part, sets out to investigate the use of Non-Destructive Testing (NDT) Techniques for in-line quality control of processing steps in the fabrication of thin film photovoltaics. It is a growing trend to utilize NDT techniques for process control as opposed to the traditional method of applying NDT on completed products.  
Electrical characterization based on current-voltage (IV) measurement can provide information on the overall functionality of the optoelectronic devices and provide information about the malfunction of the device but not the location of the problem [11]. Electro-optical imaging techniques such as light beam induced current (LBIC) mapping, dark lock-in thermography (DLT), electroluminescence (EL) imaging, and photoluminescence (PL)imaging are able to reveal the details on registration, defects, particles, shunts and processing variations affecting electrical functionality [12; 13; 14; 15]. These techniques have also proven useful for inline inspection, monitoring and process control [12; 16; 17; 18; 19].  
In this study, the DLIT method was investigated as a potential in-line inspection method for qualification of fabrication steps in thin film photovoltaic processes, as DLIT can be used as a quality control method for both devices and individual layers involved in the full device stack. The in-house developed DLIT system was validated in the laboratory trials where printing defects and variation in the print quality of silver printed conductors on thin film samples were detected.  
A new automated defect recognition (ADR) methodology for inspection of the printed conductive thin films, which is based on segmentation and thresholding methods is proposed. The thermal image post-processing procedure involves two main stages:  
Stage 1: Each individual silver printed conductive wire was identified by using image segmentation. This was compared with the designed printing patterns which enabled the completely broken wires to be automatically detected;  
Stage 2: Within the identified printed conductors, the local electrical defects on the thin film, which are shown as hot spots in the thermal images, were automatically detected using the thresholding method.  
The remainder of this paper is structured as follows; in Sections 2 and 3, the in-house developed DLIT inspection system, the laboratory-based validation trials are introduced. Section 4 describes the proposed ADR algorithms with block schematic diagrams of the localized segmentation and thresholding methods. Section 5 presents the results of ADR from DLIT images acquired from validation trials. The conclusions are summarized in Section 6.