M. Sakthivel ¹, D. Dhayalan ¹, M. Saleem Babu ², J. Senthil Murugan ¹

Affiliations
1 Department of MCA, Vel Tech High Tech Engineering College, Chennai - 600062, Tamil Nadu, IN
2 Department of CSE, Jaya Engineering College, Chennai - 602024, Tamil Nadu, IN

Abstract

Background: Aircraft Recognition with high resolution space borne images is a challenging task.It is different from other natural object recognition. The ground image of aircraft is complex and disturbing. The target image has to be detected in a cluttered background. Methods: The proposed technique takes into account multiple features such as circular Frequency filter (CF-filter), fuselage symmetry and angle between fuselage axis and wing for candidate selection. Normalized Tree cut algorithm isused for Segmentation of image done and aircraft alignment done using Histogram Oriented Gradient (HOG). Automatic jigsaw puzzle solution is implemented for aircraft reconstruction of pieces. Findings: In the candidate selection stage because of cluttered background the aircraft is not identified. Here the multiple identification techniques such ascircular frequency filter (CF-filter), fuselage symmetry and angle between fuselage axis and wing are considered. Applications: The above said techniques were dealt earlier as independent features. Because of proposed multiple feature consideration accuracy in candidate identification is enhanced.

Keywords

Aircraft Recognition, Jigsaw Puzzle Algorithm, Histogram Oriented Gradient

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D. Dhayalan ¹, K. Divya Bharathi ¹, S. Radhika ¹, V. Rajalakshmi ¹

Affiliations
1 Department of MCA, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai - 600 062, Tamil Nadu, IN

Abstract

Objectives: This paper discusses about the importance of the effective intelligence among human and artificial devices. Nowadays more and more human activities will be carried by artificial agents and devices, which overcome our Imagination. Methods: This paper gives a theoretical application to develop the personality of mentally challenged person by feeding Artificial Instructions into their brain by using the fMRI (functional Magnetic Resonance Imaging) concept in the reverse manner which is used in the mind reading system. Findings: The instructions will get fed into the brain by means of computer system and then it passes to the Temporal lobes of the human brain.Temporal lobes were used to speak, make decision, think and analyse. The instructions will get decoded into brain instruction by the different signals of the fMRI. Applications/Improvements: This work may bring changes in the life of mentally challenged ones and accidental victims.

Keywords

Artificial Instructions, fMRI Technology, Functional Imaging, Human Brain

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D. Dhayalan ¹, M. Yuvarani ¹, A. Nishanthi ¹, M. Sathiya ¹, T. Ranjani ¹

Affiliations
1 Department of MCA, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai - 600062, Tamil Nadu, IN

Abstract

Objective: In this paper, we deliver a concept based on image and video processing designs on behalf of eyesight else vision find out. Methods: The inducement of the study is for disabled people, without their hands. The vision checkup method is by using the mobile phone interaction. It utilizes the detected face location and vision detection is based on mobile phones for controlling eyelids state (close or open). Findings: This vision checkup method is used to show the improvement of accuracy of detection. In this mobile application, the light effect and the spaces among the disabled person eyes is tracking. The correctness of vision detection will be given by the usage of mobile devices. In existing, phone-based vision test for patients who wants to track their eyesight in their place itself, this type of gadgets could help to track people who are having defects in their eye before they lost more vision, and take the treatment in proposed this same tool could help the disabled persons also by using image processing of vision detection in eyelids state (close or open) detection. Improvements: The drawbacks are reduced in this proposed system. Finally, it provides the 99% of result for the complete detection of accurateness.

Keywords

Detection Accuracy, Eye Blink, Eye Checkup, Mobile Interaction, Vision Detection

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