College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Computer science & Sliding mode control. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

Temperature Estimation of Visible Heat Sources by Digital Photography and Image Processing

Abstract: This paper proposes a novel noncontact temperature measurement technique using a consumer-grade digital still camera. The images of various visible heat sources are captured. Using color image segmentation, source zones are identified. The actual temperature is measured by placing a miniature thermocouple in each zone. The color temperature correlation is established by applying various analytical techniques. Different equations are formulated for different zones observing color dominance in the respective zone. The results indicate that the image-based measurements agree with the corresponding contact measurements within an error range of about ±5% for most of the sources. The technique is successfully used for measuring the temperature distribution of different industrial applications, like muffle furnace, salt bath furnace, induction furnace, etc.

Framework for client side AES encryption technique in cloud computing

Abstract: Now a days, cloud computing is most popular network in world. Cloud computing provides resource sharing and online data storage for the end users. In existed cloud computing systems there are many security issues. So, security becomes essential part for the data which is stored on cloud. To solve this problem we have proposed this paper. This paper presents client side AES encryption and decryption technique using secret key. AES encryption and decryption is high secured and fastest technique. Client side encryption is an effective approach to provide security to transmitting data and stored data. This paper proposed user authentication to secure data of encryption algorithm with in cloud computing. Cloud computing allows users to use browser without application installation and access their data at any computer using browser. This infrastructure guaranteed to secure the information in cloud server.

Robot based indoor autonomous trash detection algorithm using ultrasonic sensors

Abstract: Autrebot; indoor trash detection and collection system using autonomously directed robotic exploration algorithm is presented. The algorithm has linear time complexity and is developed using two ultrasonic sensors. The key feature of this algorithm is the acquisition of object location based on the sensor output. The two sensor interface is specially implemented for intelligent decision making and proper identification of the object of interest, ignoring stray mobile objects or walls. Pneumatic actuators are used for the pickup and disposal of trash once it has been successfully located. Experiments with the algorithm have been conducted in static as well as dynamic environments and its performance analyzed for multiple scenarios. The algorithm can be thus extended for locating a particular object of interest based on its physical attributes.

Fast face recognition based on Wavelet Transform on PCA

Abstract: Today the word is moving towards the globalization in area of biometrics as an individual identification method. The techniques which are established for an identifying the individual using face as a biometric has become more importance in field of biometrics. The face database extracted leads the many application like photography, security surveillance, database identification etc. This paper includes the study of facial feature extraction techniques that are Principal Component Analysis (PCA) and Discrete Wavelet Transforms (DWT), hear the comparison of two given algorithms have been made with concerned to the rate of feature extraction for face recognition using the Principal Component Analysis (PCA) and the PCA using Discrete Wavelet Transforms (DWT). The proposed algorithm uses the concept of DWT for the image compression and PCA for the feature extraction and identification method. The limitations of the only PCA algorithm are a poor recognition speed and complex mathematical calculating load. To eliminate these limitations we are applying the DWT with different decomposition levels, i.e from level 0 to level 3 to facial image by using Daubechies Transform and applying the PCA for feature extraction process. The Euclidean Distance Measures system is used to find the nearest matching features in the whole database. In this paper the the mentioned algorithms are compared with their feature extraction and recognition time, the second parameter is the percentage of recognition of a test image. The results shows that the PCA with DWT applied gives higher recognition rate up to 93% than only PCA, with very less access time.