A Machine Learning Approach to Design of Aperiodic, Clustered-Dot Halftone Screens via Direct Binary Search.

Aperiodic, clustered-dot, halftone patterns have recently become popular for commercial printing of continuous-tone images with laser, electrophotographic presses, because of their inherent stability and resistance to moiré artifacts. Halftone screens designed using the multistage, multipass, clustered direct binary search (MS-MP-CLU-DBS) algorithm can yield halftone patterns with very high visual quality. But the characteristics of these halftone patterns depend on three input parameters for which there are no known formulas to choose their values to yield halftone patterns of a certain quality level and scale. Using machine learning methods, two predictors are developed that take as input these three parameters. One predicts the quality level of the halftone pattern. The other one predicts the scale of the halftone pattern. To provide ground truth information for training these predictors, human subjects viewed a large number of halftone patches generated from MS-MP-CLU-DBS-designed screens and assigned each patch to one of four quality levels. For each patch, the location of the peak in the radially averaged power spectrum (RAPS) is calculated as a measure of the scale or effective line frequency of the pattern. Experimental results demonstrate the accuracy of the two predictors and the effectiveness of screen design procedures based on these predictors to generate both monochrome and color high quality halftone images.

Machine Learning Algorithms for Classification of First-Trimester Fetal Brain Ultrasound Images.

OBJECTIVE: To evaluate the feasibility of machine learning (ML) tools for segmenting and classifying first-trimester fetal brain ultrasound images. METHODS: Two image segmentation methods processed high-resolution fetal brain images obtained during the nuchal translucency scan: "Statistical Region Merging" (SRM) and "Trainable Weka Segmentation" (TWS), with training and testing sets in the latter. Measurement of the fetal cerebral cortex in original and processed images served to evaluate the performance of the algorithms. Mean absolute percentage error (MAPE) was used as an accuracy index of the segmentation processing. RESULTS: The SRM plugin revealed a total MAPE of 1.71% ± 1.62 SD (standard deviation) and a MAPE of 1.4% ± 1.32 SD and 2.72% ± 2.21 SD for the normal and increased NT groups, respectively. The TWS plugin displayed a MAPE of 1.71% ± 0.59 SD (testing set). There were no significant differences between the training and testing sets after 5-fold cross-validation. The images obtained from normal NT fetuses and increased NT fetuses revealed a MAPE of 1.52% ± 1.02 SD and 2.63% ± 1.98 SD. CONCLUSIONS: Our study demonstrates the feasibility of using ML algorithms to classify first-trimester fetal brain ultrasound images and lay the foundation for earlier diagnosis of fetal brain abnormalities.

New Design for Compact Color Screen Sets for High-End Digital Color Press.

Digital halftoning is an essential part of the process for printing color, continuous-tone content. Traditionally, the highest quality has been achieved with analog, offset lithographic presses, using color screen sets that yield periodic, clustereddot halftone patterns. Increasingly, these systems are being supplanted by digital presses that are based on either electrophotographic or inkjet marking processes. Due to the inherent instability of the electrophotographic marking process, periodic, clustered-dot halftone patterns are also widely used with such presses. However, digital presses have much lower resolution than their analog counterparts. Simply mimicking the traditional screen designs used with commercial, offset presses will result in halftone patterns that are more susceptible to moire due to the interaction between the periodic patterns used to render the different color channels. This causes instability in the printed colors. The moire can be reduced by increasing the frequency of the halftone patterns. But this may make the print appear grainier than its analog counterpart. In this paper, we introduce a principled design procedure that allows one to design color screen sets that generate periodic, clustered-dot halftone patterns that improve color stability without increasing graininess. We present experimental results to support the benefits of our new color screen set design framework.

Detecting and tracking moving objects in long-distance imaging through turbulent medium.

The challenge of detecting and tracking moving objects in imaging throughout the atmosphere stems from the atmospheric turbulence effects that cause time-varying image shifts and blur. These phenomena significantly increase the miss and false detection rates in long-range horizontal imaging. An efficient method was developed, which is based on novel criteria for objects' spatio-temporal properties, to discriminate true from false detections, following an adaptive thresholding procedure for foreground detection and an activity-based false alarm likeliness masking. The method is demonstrated on significantly distorted videos and compared with state of the art methods, and shows better false alarm and miss detection rates.

Effects of image restoration on automatic acquisition of moving objects in thermal video sequences degraded by the atmosphere.

We aim to determine the effect of image restoration (deblurring) on the ability to acquire moving objects detected automatically from long-distance thermal video signals. This is done by first restoring the videos using a blind-deconvolution method developed recently, and then examining its effect on the geometrical features of automatically detected moving objects. Results show that for modern (low-noise and high-resolution) thermal imaging devices, the geometrical features obtained from the restored videos better resemble the true properties of the objects. These results correspond to a previous study, which demonstrated that image restoration can significantly improve the ability of human observers to acquire moving objects from long-range thermal videos.