2D Geometric Object Shapes Detection and Classification

Abstract

In computer vision, object detection is a basic process for advanced procedure forms such as object detecting, analyzing, tracking, etc., for further processes, features extraction play a vital part to identify the objects accurately. Most of the existing frameworks may not be able to distinguish the objects appropriately when different objects have a place to a single frame. In this work, an automatic detection and recognition system of two-dimensional geometric shapes have been proposed. Firstly applied Genetic Algorithm (GA) to fill the shape after performing proper segmentation pre-processing method. The proposed framework is able of identifying numerous objects in the input image, determining the sort of the identified object, and labeled the recognized objects. Statistical method has been applied for each shape to extract the objects corners' points by calculating the largest boundary to form the features vector. Ultimately, the identified objects are classified as geometrical shapes such as square, rectangular, triangular, or circular. The proposed method achieved high accuracy around 98.3%, and an average computational time 0.521 sec. as an effective classification technique.

A Comprehensive Review of Load Frequency Control Technologies

“…The structure of the controllers considered in [220] is much simpler and can be more readily implemented since, unlike methods presented in previous papers, where either an optimal state feedback law or a state estimator is used; the technique proposed in [220] uses only the directly measurable system state variables. A sub-optimal AGC regulator design for a two-area interconnected power system using a constrained feedback control strategy is presented in [221]. The power system dynamic performance is analyzed based on time response plots achieved with the implementation of designed optimal and sub-optimal AGC regulators in the wake of 1% load disturbance in one of the areas.…”

“…The power system dynamic performance is analyzed based on time response plots achieved with the implementation of designed optimal and sub-optimal AGC regulators in the wake of 1% load disturbance in one of the areas. Another version of the paper [221], which uses a sub-optimal AGC method, is presented in [162]. The authors used an output feedback control strategy, which has been applied in designing a regulator for a two-area interconnected power system.…”

Burning Skin Detection System in Human Body

“…Researchers are developing automated burn wound analysis systems due to the subjectivity of this approach. These systems should include three major components: burn image segmentation, feature extraction (Hasan, Ibraheem and Abdulhadi , 2022), and classification of segmented regions into healthy skin, and burned skin. (Liu, et al, 2021) introduced a review of some common ideas and characteristic features of medical image segmentation based on deep learning algorithms by applying the segmentation method for different human organs areas such as brain tumors, lung nodules, eyes, chest, heart, abdomen, and some other parts besides, whereas (Liangrui, Zhichao and Shaoliang, 2022) reviewed an investigation on various methods in pathology in a pathological and technical perspective.…”