CENTRE FOR IMAGE PROCESSING

About Centre

The Centre for Image processing is initiated to motivate modern thinking, designing and implementing ideas in the field of Image Processing. The center is dedicated to develop modern & efficient image processing techniques, imaging systems, and their applications to information engineering, biology, and medical science.

Objectives of the Centre

• The objective is to study and understand the basics of images, image processing and software tools used to implement various algorithms and to implement computer vision techniques with emphasis on practical aspects.
• Collaborate and work with various agencies in the field of Image processing and also suggest our service to various scientific institutions.
• To conduct and organize various Technical seminars/workshops in the field of Image Processing.

Facilities Available

• Server Configuration and Software
• Server Board: S2600WFT
• Processor: Intel Xeon Silver4210 CPU @2.20GHZ 2.19GHZ
• RAM: 64 GB HDD :1863 GB
• Scilab 6.1.1
• Matlab

Details of Completed/Ongoing Projects

1. Predicting bone density of a person using CT Images Bone density, or bone mineral density (BMD), is the amount of bone mineral in bone tissue. The concept is of mass of mineral per volume of bone (relating to density in the physics sense), although clinically it is measured by proxy according to optical density per square centimeter of bone surface upon imaging

2. Knee fracture Identification from X ray Images Bone fracture is a common problem due to pressure, accident and osteoporosis. Moreover, bone is rigid portion and supports the whole body. Therefore, the bone fracture is taken account of the important problem in recent year. Lower leg bone (Tibia) fracture types recognition is developed using various image processing techniques. The purpose of this work is to detect fracture or non-fracture and classify type of fracture of the lower leg bone (tibia) in x-ray image.

3. Retinal Image Processing With Defect Detection Using AI Many important eye diseases as well as systemic diseases manifest themselves in the retina. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed.

4. Lung Cancer Detection and classification Lung cancer is one of the most common diseases among humans and one of the major causes of growing mortality. Medical experts believe that diagnosing lung cancer in the early phase can reduce death with the illustration of lung nodule through computed tomography (CT) screening. Examining the vast amount of CT images can reduce the risk.

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