Unsupervised range-constrained thresholding.
ABSTRACT Three range-constrained thresholding methods are proposed in the light of human visual perception. The new methods first implement gray level range-estimation, using image statistical characteristics in the light of human visual perception. An image transformation is followed by virtue of estimated ranges. Criteria of conventional thresholding approaches are then applied to the transformed image for threshold selection. The key issue in the process lies in image transformation which is based on unsupervised estimation for gray level ranges of object and background. The transformation process takes advantage of properties of human visual perception and simplifies an original image, which is helpful for image thresholding. Three new methods were compared with their counterparts on a variety of images including nondestructive testing ones, and the experimental results show its effectiveness.
- [Show abstract] [Hide abstract]
ABSTRACT: Introducing more information to improve the segmentation quality was regarded as an effective way, such as three-dimensional Otsu thresholding. However, it should be led to be very time consuming for real-time applications, and the Otsu criterion is questionable in some cases, for example, nondestructive testing. In the paper, a novel mechanism based on data field, originated from physical fields, is proposed for three-dimensional thresholding. Without any explicit criterions, an optimal threshold vector is produced using the self-adaptive evolution of data particles in the data field. And the proposed method has low time complexity. Experimental results, compared with the state-of-art algorithms and the related methods, suggest that the new proposal is efficient and effective.Neurocomputing. 11/2012; 97:278–296.
Conference Paper: Analysis of Solder Paste scooping with hierarchical point processes.[Show abstract] [Hide abstract]
ABSTRACT: In this paper we introduce a probabilistic approach for optical quality checking of Solder Pastes (SP) in Printed Circuit Boards (PCB). Dealing with unregistered image inputs, the task is to address at the same time SP identification, and detecting special soldering errors, called scooping. For this reason we introduce a novel Hierarchical Marked Point Process (HMPP) framework, which is able to handle the paste and scooping extraction problems simultaneously, so that the SPs and the included scoops have a parent-child relationship. A global optimization process attempts to find the optimal configuration of entities, considering the observed data, prior knowledge, and interactions between the neighboring circuit elements. The proposed method is evaluated on a real PCB image set containing more than 3000 SPs and 600 scooping artifacts18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, September 11-14, 2011; 01/2011
- [Show abstract] [Hide abstract]
ABSTRACT: Thresholding methods based on entropy have been proposed and developed over the years. In this paper, an improved Tsallis entropy based thresholding method is proposed for segmenting the images which presenting local long-range correlation rather than global long-range correlation. The advantage of the proposed method is to distinguish the pixels' local long-range correlation by the nonextensive parameter q. And the experimental results of various infrared images as well as nondestructive test ones show the effectiveness of the proposed method.Signal Processing. 12/2012; 92(12):2931–2939.