The Braille Recognition System is the process of capturing a Braille document image and turning its content into its equivalent natural language characters. The Braille Recognition System's cell transcription and Braille cell recognition are the two basic phases that follow one another. The Braille Recognition System is a technique for locating and recognizing a Braille document stored as an image, such as a jpeg, jpg, tiff, or gif image, and converting the text into a machine-readable format, such as a text file. BCR translates an image's pixel representation into its character representation. As workers at visually impaired schools and institutes, we profit from Braille recognition in a variety of ways. The Braille Recognition System contains many stages, including image acquisition, pre-processing of images, and character recognition. This review aims to examine the earlier studies on transcription and Braille cell recognition by other scholars and the comparative results and detection techniques among them. This review will look at previous work done by other researchers on Braille cell recognition and transcription, comparing previous works in this study, and will be useful and illuminating for Braille Recognition System researchers, especially newcomers.
Nathaniel Hawthorne (1804-1864) has been widely known for his special interest in the female characters. In many of his novels, he narrates the conditions, values, and the institutions that surround and control the life of women, leading them to be victims. In “Rappaccini’s Daughter” (1844), the heroine, Beatrice is created to be victimized by her loved ones (her father and lover). This paper focuses on the term “victim,” it shows its aspects through the development of Beatrice’s character. The paper also studies a female character in the male-dominated society, to show the cruelty done to her, and how she is considered to be a second rate person, who is unable to live normally, or at least to save herself from dea
... Show MoreCloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications. This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit
... Show MoreThe current study monitors the mechanisms of formation of the actor's performance expressive system (voice and motion) and the levels of their construction consistent with the aesthetic premise of the theatrical performance through incorporating what is natural, materialistic (physiological) and artistic and philosophical virtual (aesthetic ), through which the creative actor seeks not to repeat the image and substance of a thing according to its natural life image, in favor of new aesthetic reproduction governed by a group of significant relationships formed according to (artistic and philosophical) characteristics and features that distinguish the artistic accomplishment from its reality(its natural and functional reference). According
... Show MoreThis paper presents an approach to license plate localization and recognition. A proposed method is designed to control the opening of door gate based on the recognition of the license plates number in Iraq. In general the system consists of four stages; Image capturing, License plate cropping, character segmentation and character recognition. In the first stage, the vehicle photo is taken from standard camera placed on the door gate with a specific distance from the front of vehicle to be processed by our system. Then, the detection method searches for the matching of the license plate in the image with a standard plate. The segmentation stage is performed by is using edge detection. Then character recognition, done by comparing with templ
... Show MoreFacial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f
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