Depth estimation of metallic objects using multiwavelets scale-space representation

The problem of dimensional defects in aluminum die-castings is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic with highly reflective nature, it is extremely hard to estimate true dimensionality of these metallic parts, autonomously. Some existing vision systems are capable of estimating depth to high accuracy, however are very much hardware dependent, involving the use of light and laser pattern projectors, integrated into vision systems or laser scanners. However, due to the reflective nature of these metallic parts and variable factory environments, the aforementioned vision systems tend to exhibit unpromising performance. Moreover, hardware dependency makes these systems cumbersome and costly. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a pair of stereo cameras and a defused fluorescent light. The proposed vision system is capable of estimating surface depths within the accuracy of 0.5mm. In addition, the system is invariant to illuminative variations as well as orientation and location of the objects on the input image space, making the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup. The proposed system is a major part of quality inspection system for the automotive manufacturing industry. <br /

Stereo correspondence estimation using multiwavelets scale-space representation-based multiresolution analysis

A multiresolution technique based on multiwavelets scale-space representation for stereo correspondence estimation is presented. The technique uses the well-known coarse-to-fine strategy, involving the calculation of stereo correspondences at the coarsest resolution level with consequent refinement up to the finest level. Vector coefficients of the multiwavelets transform modulus are used as corresponding features, where modulus maxima defines the shift invariant high-level features (multiscale edges) with phase pointing to the normal of the feature surface. The technique addresses the estimation of optimal corresponding points and the corresponding 2D disparity maps. Illuminative variation that can exist between the perspective views of the same scene is controlled using scale normalization at each decomposition level by dividing the details space coefficients with approximation space. The problems of ambiguity, explicitly, and occlusion, implicitly, are addressed by using a geometric topological refinement procedure. Geometric refinement is based on a symbolic tagging procedure introduced to keep only the most consistent matches in consideration. Symbolic tagging is performed based on probability of occurrence and multiple thresholds. The whole procedure is constrained by the uniqueness and continuity of the corresponding stereo features. The comparative performance of the proposed algorithm with eight famous existing algorithms, presented in the literature, is shown to validate the claims of promising performance of the proposed algorithm. <br /

Constructing artificial images of facial expressions

This paper presents a method for construction of artificial images of facial expressions. The proposed fractal-based synthesis procedure called pixel-based correspondence works on 2D images and does not require any depth information. This method can generate artificial images of an object when only a single image is given. Using the proposed method, effective example-based facial analysis systems can be trained and utilised in various applications.<br /

Comments on \u27Information measure for performance of image fusion\u27

The unsuitability of using classic mutual information measure as a performance measure for image fusion is discussed. Analytical proof that classic mutual information cannot be considered a measure for image fusion performance is provided.<br /

Application of co-operative agents in handling fluctuations in a pull production system

This paper presents the general details of the structure and strategy of a multi-agent system that is being developed to improve the performance of pull (kanban) production control to handle large fluctuations in product demand. Employing a set of generic, heterarchial agents each controlling a single product and co-operating together to ensure that all components, regardless of demand fluctuation, are manufactured on time as per basic kanban principles. Preliminary results indicate that the basic kanban model does not cater for large demand fluctuations and the application of this multi-agent strategy may be beneficial to improving the overall system performance and increase the likelihood that all products will be manufactured on time.<br /

Effective Vehicle-Based Kangaroo Detection for Collision Warning Systems Using Region-Based Convolutional Networks.

Traffic collisions between kangaroos and motorists are on the rise on Australian roads. According to a recent report, it was estimated that there were more than 20,000 kangaroo vehicle collisions that occurred only during the year 2015 in Australia. In this work, we are proposing a vehicle-based framework for kangaroo detection in urban and highway traffic environment that could be used for collision warning systems. Our proposed framework is based on region-based convolutional neural networks (RCNN). Given the scarcity of labeled data of kangaroos in traffic environments, we utilized our state-of-the-art data generation pipeline to generate 17,000 synthetic depth images of traffic scenes with kangaroo instances annotated in them. We trained our proposed RCNN-based framework on a subset of the generated synthetic depth images dataset. The proposed framework achieved a higher average precision (AP) score of 92% over all the testing synthetic depth image datasets. We compared our proposed framework against other baseline approaches and we outperformed it with more than 37% in AP score over all the testing datasets. Additionally, we evaluated the generalization performance of the proposed framework on real live data and we achieved a resilient detection accuracy without any further fine-tuning of our proposed RCNN-based framework

Karyology of Abramis brama in the southern waters of Caspian sea

The karyology of bream (Abramis brama) were done for the first time in Iran. This study was conducted on chromosomal number, chromosome arms and karyotyping of bream from the -Southern part of the Caspian Sea with preparing chromosomal extensions on the base of Squash method. The number of metaphase plates using Squash method on renal and gill tissues was determined as to be 2n=50 and the number of chromosome arms was NF=82. The prepared karyotype of this species was consisted of 8 pairs of metacentric, 8 pairs of submetacentric and 9 pairs of acrocentric chromosomes

Haptic control methodologies for telerobotic stair traversal

Teleoperated mobile robots provide the ability for a human operator to safely explore and evaluate hazardous environments. This ability represents an important progression towards the preservation of human safety in the inevitable response to situations such as terrorist activities and urban search and rescue. The benefits of removing physical human presence from such environments are obvious, however challenges inhibiting task performance when remotely operating a mobile robotic system need to be addressed. The removal of physical human presence from the target environment introduces telepresence as a vital consideration in achieving the desired objective. Introducing haptic human-robotic interaction represents one approach towards improving operator performance in such a scenario. Teleoperative stair traversal proves to be a challenging task when undertaking threat response in an urban environment. This article investigates the teleoperation of an articulated track mobile robot designed for traversing stairs in a threat response scenario. Utilising a haptic medium for bilateral human-robotic interaction, the haptic cone methodology is introduced with the aim of providing the operator with a vision-independent, intuitive indication of the current commanded robot velocity. The haptic cone methodology operates synergistically with the introduced fuzzy-haptic augmentation for improving teleoperator performance in the stair traversal scenario.<br /