•Proposed optimized multispectral system tree species classification performances were investigated.•Showed that proposed system is robustness for change in spatial scale.

Projects: 1. Processing and analysis of airborne hyperspectral images for tree species classification. (Optimize airborne hyperspectral data for tree species classification)Task Performed• Applied radiometric correction, atmospheric correction, data denoising and view-illumination correction method while processing images. • Applied feature selection methods (e.g, Fisher score, Information Gain, Sparse regression-based methods) and feature extraction methods (e.g.,SVD,PCA,ICA,MNF) to reduce the data dimensionality for data analysis.• Propose and simulate the different airborne multispectral sensor sensitivity responses and investigate data classification performance with simulated responses.• Investigate supervised object classification performance applying Support vector machine and Discriminate analysis classifier. 2. Study of Variance in color of Eucalyptus spp. CloneTask Performed• Analyzed spectral data acquired from different Eucalyptus spp. and from different tree location (Pitch, half radius, and bark)• Implement spectral to RGB and La*b* color space conversion and investigate color variance in tree locations. • Investigate spectral classification between Eucalyptus spp.

Project: ArcGIS Add-in Development in .net• Defined application problems by consulting with clients to evaluate procedures and processes.• Collaborated with designers to create clean interfaces and simple, intuitive interactions and experiences.• Tested programs to validate results.• Scrum method was used in the software development cycle while working with team in different locations.

1. Spectral Analysis and Classification of Dirt Particles in Pulp Task Performed• Imaging Device calibration .• Spectral image was acquired from pulp at a different stage of pulp processing for paper production.• Analyzed Spectral data was to compute high contrast images.• Applied different image thresholding, edge detection, morphological processing to enhance image for dirt particle counting.• Investigate dirt particle classification. Feed-forward neural network and discriminate analysis classifier, KNN classifier were applied. In • Performance fluorescence measurement and simulate paper fluorescence under different Illuminate condition. • Develop GUI application to visualized dirt particle classification results.

Projects:1. Analysis of Eye bottom spectral images (Retinal Image) to investigate diabetic retinopathyTask Performed• Applied image processing and a signal processing method to a analyze quality of acquired retinal image. • Applied statistical and multivariate analysis method to investigate diabetic retinopathy in eye bottom images. 2. Spectral estimation from RGB imageTask Performed• Applied polynomial regression, radial basis function and Wiener estimation method for spectral estimation from RGB images using global (Munsell, Macbeth color checker, etc.)

• Defined application problems by consulting with clients to evaluate procedures and processes.• Processed power line LiDAR to segments object based on shape .• Tested programs to validate results.

1. Spectral Imaging in Natural Scenes Task Performed• Comparative study of Natural Illumination reconstruction and change in Correlated Color Temperature by using PCA and ICA Features).• Implemented an algorithm to Visualization a color distribution in L*a*b* color Gamut.• Color transformation to different color space and make analysis.• Multivariate analysis of Spectral images.

Work as a color researcher in Color Research Group, at Department of Optics University de Granada.

•I join KEC as a lecture to take lecture class and laboratory exercises for bachelor of engineering Student in subject Computer graphics, Computer Networks and software engineering.• With my expertise and leadership capabilities, I was soon promoted to deputy head of the department and later to the head of the department.• Manage around 50 teaching staffs and 400 students in the department.• Inspired students to translate their academic interests into the real world by taking positive actions

Task is to give a lecture class and take tutorial and laboratory class in subject Computer graphics, Computer Networks and software engineering.