Intelligent Point Cloud Edge Detection Method Based on Projection Transformation

An edge detection method based on projection transformation is proposed. First, the vertical projection transformation is carried out on the target point cloud. Data X and data Y are normalized to the width and height of the image, respectively. Data Z is normalized to the range of 0-255, and the depth represents the gray level of the image. Then, the Canny algorithm is used to detect the edge of the projection transformed image, and the detected edge data is back projected to extract the edge point cloud in the point cloud. Evaluate the performance by calculating the normal vector of the edge point cloud. Compared with the normal vector of the whole data point cloud of the target, the normal vector of the edge point cloud can well express the characteristics of the target, and the calculation time is reduced to 10% of the original.

Assessment the Visual Clarity of the Projector in Classroom and Innovative Asymmetric Distribution LED Tube Applications

The paper aims to explore the relationship between the vertical plane luminance on projection screens and human visual clarity in the classroom or meeting room. While controlling the lighting environment conditions of the classroom to create different luminous distributions and luminance on the projection screen, a survey is conducted to understand students’ visual experience about screen clarity during the field experiment. The luminance of each picture on the projection screen is measured under the specified lighting conditions of luminaires in the classroom, and the relationship is formulated between the average luminance on the projection screen and the visual satisfaction based on clarity of experience. This will be useful for further studying the acceptable threshold of luminance distribution in the classroom to provide a better visual clarity and lighting quality of projection screens while teaching. In this study, the measurement and performance evaluation on a projection screen were carried out at a classroom in the National Taiwan University of Science and Technology (NTUST). By using an image luminance meter and analyzing the research results, we propose an improvement strategy for asymmetric luminous distribution design of LED light tube and light switch control mechanism of luminaires to resolve the inadequate luminance of the vertical projection screen area to improve the lighting quality and visual clarity of the projection screen while teaching with the least cost.

Characterizing the Validity of the Inverted Pendulum Model for Quiet Standing

By assuming that the human body rotates primarily around the ankle joint in the sagittal plane, the human body has been modelled as a single inverted pendulum (IP) to simulate the human quiet stance. Despite its popularity, the validity of the IP model has been challenged in many studies. Rather than testing the validity of the IP model as a true or false question, this work proposes a feature to quantify the degree of validity of the IP model. The development of the proposed feature is based on the fact that the IP model predicts that the horizontal acceleration of COM is proportional to the COP error which is defined as the difference between the center of pressure (COP) and the vertical projection of the center of mass (COM). Since the horizontal components of the acceleration of COM and the ground reaction force (GRF) are always proportional, the proposed feature is the correlation coefficient between the anterior-posterior (AP) components of GRF and the COP error. The efficacy of the proposed feature is demonstrated by comparing its differences for individuals in two age groups (18–24 and 65–73 years) in quiet standing. The experimental results show that the IP model is more suited for predicting the motion of the older group than the younger group. Our results also show that the proposed feature is more sensitive to aging effects than one of the most reliable and accurate COP-based postural stability features.

EXPLOITABLE EDGE ANALYSIS FOR FREE FLOW VEHICLE PLATE LOCALIZATION

In Malaysia, vehicle recognition system (VRS) such as vehicle plate recognition and counting, is rapidly growing and applied in many areas such as to identify vehicle identities for the law enforcement by authorities and electronic toll collection by highway agencies. Uncovering the region of interest in chaotic illumination environment at free flow road makes localizing license plate is critical process of VRS. Available edge vertical projection claimed to be robust to illumination, however, it tends to create false edges and sensitive to noises that can hinder the recognition performance. Thus, this research aims to propose a license plate localization method that based on exploitable edge analysis.comprising four main steps, namely pre-processing, rectangular blob searching, analysis and the vertical rectangular blobs projection. It calculates total and exploit edge information at y axis of the image. The proposed method is then tested on the European number plate datasets i.e. Baza Slika which contains about 167 vehicle images and Ondrej which contains about 97 vehicle images. The experimental results show that the proposed method outperforms the Ondrej method by obtaining accuracy of 95% on Baza Slika dataset and slightly lower by an accuracy of 91% on the Ondrej dataset. Then, the proposed method tested on the Malaysia vehicle dataset namely Tol Sungai Long data set which contains about 584 images of different illumination conditions, i.e. 297 images in the morning, 140 images in the afternoon and 147 images in the night. The proposed method outperforms other approaches with accuracy of 91.24%, 93.57% and 75.51% in the morning, evening and night respectively.

Investigation of ANN Architecture for Predicting Load-Carrying Capacity of Castellated Steel Beams

Castellated steel beams (CSB) are an attractive option for the steel construction industry thanks to outstanding advantages, such as the ability to exceed large span, lightweight, and allowing flexible arrangement of the technical pipes through beams. In addition, the complex localized and global failures characterizing these structural members have led researchers to focus on the development of efficient design guidelines. This paper aims to propose an artificial neural network (ANN) model with optimal architecture to predict the load-carrying capacity of CSB with a scheme of the simple beam bearing load located at the center of the beam. The ANN model is built with 9 input variables, which are essential parameters equivalent to the geometrical properties and mechanical properties of the material, such as the overall depth of the castellated beam, the vertical projection of the inclined side of the opening, the web thickness, the flange width, the flange thickness, the width of web post at middepth, the horizontal projection of inclined side of the opening, the minimum web yield stress, and the minimum flange yield stress. The output variable is the load-carrying capacity of the CSB. With the optimal ANN architecture [9-1-1] containing one hidden layer, the performance of the ANN model is evaluated based on statistical criteria such as R2, RMSE, and MAE. The results show that the optimal ANN model is a highly effective predictor of the load-carrying capacity of the CSB with the best value of R2 = 0.989, RMSE = 3.328, and MAE = 2.620 for the testing part. The ANN model seems to be the best algorithm of machine learning for predicting the CSB load-carrying capacity.

Kurdish Text Segmentation using Projection-Based Approaches

An optical character recognition (OCR) system may be the solution to data entry problems for saving the printed document as a soft copy of them. Therefore, OCR systems are being developed for all languages, and Kurdish is no exception. Kurdish is one of the languages that present special challenges to OCR. The main challenge of Kurdish is that it is mostly cursive. Therefore, a segmentation process must be able to specify the beginning and end of the characters. This step is important for character recognition. This paper presents an algorithm for Kurdish character segmentation. The proposed algorithm uses the projection-based approach concepts to separate lines, words, and characters. The algorithm works through the vertical projection of a word and then identifies the splitting areas of the word characters. Then, a post-processing stage is used to handle the over-segmentation problems that occur in the initial segmentation stage. The proposed method is tested using a data set consisting of images of texts that vary in font size, type, and style of more than 63,000 characters. The experiments show that the proposed algorithm can segment Kurdish words with an average accuracy of 98.6%.

Research on track fastener positioning method based on local unidirectional template matching

Commonly used fastener positioning methods include pixel statistics (PS) method and template matching (TM) method. For the PS method, it is difficult to judge the image segmentation threshold due to the complex background of the track. For the TM method, the search in both directions of the global is easily affected by complex background, as a result, the locating accuracy of fasteners is low. To solve the above problems, this paper combines the PS method with the TM method and proposes a new fastener positioning method called local unidirectional template matching (LUTM). First, the rail positioning is achieved by the PS method based on the gray-scale vertical projection. Then, based on the prior knowledge, the image of the rail and the surrounding area of the rail is obtained which is referred to as the 1-shaped rail image; then, the 1-shaped rail image and the produced offline symmetrical fastener template is pre-processed. Finally, the symmetrical fastener template image is searched from top to bottom along the rail and the correlation is calculated to realize the fastener positioning. Experiments have proved that the method in this paper can effectively realize the accurate locating of the fastener for ballastless track and ballasted track at the same time.

Analysis of Extraction Algorithm for Visual Navigation of Farm Robots Based on Dark Primary Colors

In order to quickly extract the visual navigation line of farmland robot, an extraction algorithm for dark primary agricultural machinery is proposed. The application of dark primary color principle in new farmland is made clearer by gray scale method, and the soil and crops are obviously separated, and the image processing technology of visual navigation line image of farmland is realized. In binary filtering of gray scale images, the maximum interclass variance method and morphological method are used respectively. The researchers use vertical projection method and least square method to the farmland interval extracted by navigation line. The farmland that needs the guide line image will be accurately located. It is found that the visual navigation extraction algorithm of farmland robot is widely used in the image extraction of navigation lines of various farmland roads and scenes compared with the traditional gray scale algorithm. Image processing has the advantages of clearer image processing.

Orchestration of D. L. Klebanov and V. M. Zolotukhin: a comparative analysis

Background. In the last two decades there was a constantly increasing scholar interest to Kharkiv school of composition as a phenomenon of Ukrainian musical culture. Despite this, a lot of unstudied questions remain, which need to be researched. This includes problems of orchestral thinking, orchestral style and orchestral writing of Kharkiv composers, particularly, D. Klebanov and V. Zolotukhin. The novelty lies in the systematization of the principles of orchestration in the symphonies of D. Klebanov (based on the symphonies 1, 3, 6, 7) and the First Symphony of V. Zolotukhin. Analysis of literature. Orchestral music of both composers is researched quite sporadically. Its several facets are studied in works by M. Cherkashyna (1968), I. Frumina (1969), O. Gusarova (1988), T. Krasnopolska (1964), Yu. Malysheva (1967), N. Ocheretovska (2007), Е. Ponomarenko (2005), O. Roschenko (2005; 2016), А. Zamotaylo (2001), O. Zinkevych (2005), I. Zolotovytska (1980), A. Dmitriyeva (2016). There is an article by H. Savchenko (2018), specially devoted to orchestration of D. Klebanov The goal of this article is to reveal the principles of orchestration in symphonies by D. Klebanov (No. 1, 3, 6, 7) and V. Zolotukhin (No. 1) in aspect of comparative analysis. In the article the author operates such methods of research as analytical, functional, and comparative. Conclusions. In results of studying of orchestral works by D. Klebanov and V. Zolotukhin (First Symphony) in aspects of orchestral thinking and principles of orchestration, we have reached the following conclusions: 1) both composers prefer a triple orchestra, which is quite flexible, in order to achieve full-bodied orchestral texture and be able to operate different timbral colours; 2) in the works of both composer, there is an inclination to equal understanding of orchestral groups, including percussion in the first Symphony by V. Zolotukhin; 3) in the vertical projection there is a differentiation of the groups through orchestral functions, which causes a great transparency of the score; 4) much more slow changes of type of a texture and timbral combinations in horizontal projection sets apart orchestration of V. Zolotukhin from orchestration of D. Klebanov; 5) overall, orchestration of V. Zolotukhin is more dense, filled with doubles, it is dominated by “large touch”, which causes continuity and smaller degree of detailing; 6) a special trait of orchestration of D. Klebanov is thinking by timbral and textural layers with obvious distinction of orchestral function between them. Inside of these layers there is an additional split of orchestral functions which causes rather rare usage of doubles between instruments of different orchestral groups. For V. Zolotukhin, thinking with clearly defined timbral and textural layers is characteristic, which tells about realisation of orchestral polyphonic thinking on the macro level or the whole texture; 7) in orchestration of both composers there is a tendency to colouring: in the First Symphony by V. Zolotukhin it is brighter and more robust due to usage of more diverse timbral palette (from piano harp, celesta to extended group of percussion).

Biomechanics of Single Stair Climb with Implications for Inverted Pendulum Modeling

Step-by-step (SBS) stair navigation is used by those with movement limitations or lower-limb prosthetics, and by humanoid robots. Knowledge of biomechanical parameters for SBS gait, however, is limited. Inverted pendulum (IP) models used to assess dynamic stability have not been applied to SBS gait. This study examined the ability of the linear inverted pendulum (LIP) model and a closed-form, variable-height inverted pendulum (VHIP) model to predict capture point stability in healthy adults executing a single stair climb. A second goal was to provide baseline kinematic and kinetic data for SBS gait. Twenty young adults executed a single step onto stairs of two heights while attached marker positions and ground reaction forces were recorded. OpenSim software determined body kinematics and joint kinetics. Trials were analyzed with LIP and VHIP models, and the predicted capture point compared to the actual center-of-pressure on the stair. Lower-limb joint moments were larger than those reported for step-over-step stair gait. Leading knee rather than trailing ankle was dominant. Center-of-mass (CoM) velocity peaked at push-off. The VHIP model accounted for only slightly more than half of the forward progression of the vertical projection of the CoM, and was not better than LIP predictions. This suggests that IP models are limited in modeling SBS gait, likely due to large hip and knee moments. The results from this study may also provide target values and strategies to aid design of lower-limb prostheses and powered exoskeletons.