Now days, Image processing finds diversified applications in almost all field of life. The success of any image processing application is depends on proper feature extraction technique. To extract good and proper features is very interesting and challenging task in the development process. It is used to describe the image based on its contents. These extracted features are used to compare, analyse and/or search the analogous images. There are various feature extraction techniques are found in the literature to design various applications. However any image processing application generates images with high dimensionality, which will be results in the low efficiency of an application. This paper provides an approach to extract features from the images using MPEG-7 feature extraction techniques. The approach discussed in the paper uses two popular MPEG-7 visual content descriptors; they are namely Edge Histogram Descriptor (EHD) and Color Layout Descriptor (CLD). The concept results in reduction of dimensions of an image to improve the efficiency of the application. It can be used as a heart to design any image processing application as well as provides strong foundation to develop variety of applications.

This work focuses on the, implementation and validation of smart public transport system as well as goods transport system based on the application of GPS (Global Positioning System) technology, GSM (Global system for mobile communication) using Cloud computing. This system has been distributed into four modules as In-Bus/truck module, Bus/truck-stand module, cloud system and user mobile apps. After initialization of In-Bus/truck module, driver gets the information regarding to the platform availability on parking zone that are assigned to it. If the platform is vacant then driver needs to park the bus/truck at said position only. The drivers may get allotted or waiting parking platform’s information through SMS or on Drivers app. The GSM integrated GPS technology can also be used to get the current location of vehicles and the available vacant seats or vacant space in truck. This information will be recorded automatically by the system. IOT module ESP12E NODEMCU is used for controlling and handling whole operations by collecting the data. This system will also guide the drivers and the bus/truck stand controller to control all vacant ports based on real time operation. One In-Bus/truck module (configured along ESP12E) needs to be installed into each vehicle to be monitored. One Bus/truck-stand module has to be installed in to each platform. Cloud system is needed to collect the whole data for big public/goods transport systems for automation of 1000s of vehicles at a time. ThingSpeak cloud is used and computing is performed by MATLAB computing. For late running, on-time running and before time running vehicles, messages are automatically sent regarding to its location and vacant seats/space. And will be displayed on rolling board on platform. Passenger/user may get the correct information by sending message on his mobile from anywhere through mobile app. Mobile app is developed to perform all the task of monitoring to passenger/user, and drivers.