GSTIN: 27AOAPK8925Q2Z8
Research Projects
Our Current Focus
PLANT DISEASE DETECTION AND CLASSIFICATION
​Data mining technologies has been incorporated in the agriculture industry. This project implements an innovative idea to identify the affected crops and provide remedy measures to the agricultural industry. We uses technique which is used for automatic detection and classification of plant leaf diseases. Image segmentation, which is an important aspect for disease detection in plant leaf disease, is done by using genetic algorithm. Besides, digital image processing, mathematical statistics, plant pathology, and other relative fields are also considered.
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By the use of k-mean clustering algorithm, the infected region of the leaf is segmented and analyzed. This approach can significantly support an accurate detection of leaf disease. There are five steps for the leaf disease identification which are said to be image acquisition, image pre-processing, segmentation, feature extraction, classification.
The images are fed to our application for the identification of diseases. It provides a good choice for agriculture community particularly in remote villages. It acts as an efficient system in terms of reducing clustering time and the area of infected region. Feature extraction technique helps to extract the infected leaf and also to classify the plant diseases.
FACE IDENTIFICATION AND RECOGNITION
We introduces the specific face recognition technology which is based on embedded platform and puts forward a solution, which stresses on face detection algorithm, face recognition algorithm, and application development. This technology makes full use of the advantage of PCA algorithm on feature extraction and the advantages (such as fast detection speed and high detection rate) of AdaBoost algorithm based on Haar. A set of embedded face recognition system based on Tiny6410 embedded platform is realized. After face recognition testing, the results showed that this system runs stably and has high recognition rate. Thus, it can be widely used in the Things of Internet that needs to verify user identification through portable and mobile methods and in Intelligent Transportation System that needs face recognition technology. In the future research, the Cortex A8 embedded platform that has better ability of floating-point operation will be applied in the system in order to further improve the overall performance of the system. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication.
The goal of our research work is to evaluate various face detection and recognition methods, provide complete solution for image based face detection and recognition with higher accuracy, better response rate as an initial step for video surveillance. Solution is proposed based on performed tests on various face rich databases in terms of subjects, pose, emotions, race and light.
VOICE & SPEECH RECOGINATION
Upcoming Research Project
The objective of this project is to present the concepts about Speech Recognition Systems starting from the evolution to the advancements that have now been adapted to the Speech Recognition Systems to make them more robust and accurate. This project has the detailed study of the mechanism, the challenges and the tools to overcome those challenges with a concluding note that would ensure that with the advancements of the technologies, this world is surely going to experience revolutionary changes in the near future.
Our research reviews the advances that have taken place after the development of traditional Speech Recognition Systems, also this research briefly makes a quick comparison between the algorithms and the models that were and now are being used to implement these Speech Recognition Systems. Many tools and framework have been developed to overcome the challenges with Speech Recognition Systems like Voice Activity Detector, AURORA framework, etc. Technological advances in computation has led the technology of Speech Recognition reach the state where situations are far better as they were used to be years back and definitely in the coming few years the world is about to experience much better language understanding by the machines.