An Automatic Inspection Method for the Fracture Conditions of Anisotropic Conductive Film in the TFT-LCD Assembly Process

Abstract

In this study an automatic optical inspection system is presented to evaluate the fracture and deformation status of conducting particles of anisotropic conductive film in the TFT-LCD assembly process. The amount of deformation and quantity of conducting particles in the test pattern can be automatically evaluated by image analysis. A specific operation is carried out in the image processing method, and the calculation of the image gradient operator is used to produce a preferable contrast between the processed particle image and the background. The thinning processing method is applied for information reduction and information creation. An amount of samples are taken with a target template for synchronous multiple-comparison, and the optimal threshold of the binary image is obtained. This study utilizes the assistance of image processing technology to inspect the fracture conditions of anisotropic conductive film in the TFT-LCD assembly process. This system can decrease the defection rate of products, obtain over 90% recognition accuracy even in noisy environments, and will be verified in an automatic production line.

A composite light emitting device for sunset emulator with energy variation logic control algorithm

“…The overall optical field combination should be very similar to the sunset spectrum. The rays through the diffuser become soft and uniform [16].…”

Detection of Conductive Particles in TFT-LCD Circuit Using Generative Adversarial Networks

“…Particle inspection aims to estimate the distribution and quantity of validly deformed particles and then to determine whether a good conductive circuit is formed between IC and glass substrate [7], [9]. Many works have devoted to the research of automatic particle detection [7], [9]- [11]. These works are reviewed briefly as follows.…”

“…For instance, a standard template of the validly deformed particle is constructed and template matching [7] is applied to detect the presence of the particles. In the work of Lin et al [9], the particle features are extracted with the Prewitt operators. Then Otsu algorithm [12] is used to obtain the binarized image.…”

“…After binarizing the image with Otsu, the effective particles are identified by template matching method. Inspired by the approach [9], Yu-ye et al [10] acquire particle features with the background mask method rather than Prewitt operators, which reduces background noise. Then K-means clustering algorithm is applied to classify the particle pixels, which is more accurate for the overlapping particles.…”

Improvement of TFT-LCD's polarizer plate bubble problem using a preheating-process

“…In the LCD polarizer plate attaching process, the prevalent problem of bubbles between the glass substrate and the polarizer plate, due to uneven attachment, often causes quality deviations in the LCD of color image light leakage. Lin et al proposed a method to evaluate the fracture and deformation status of conducting particles of anisotropic conductive lm in the TFT-LCD assembly process [3]. Takatsuji and Arai found that holes in Al thin lms will a ect the TFT characteristics [4].…”