Pre-processing colour images with a self-organising map: baking curve identification and bake image segmentation

نویسندگان

  • Leonard G. C. Hamey
  • Jeffrey C.-H. Yeh
  • Tas Westcott
  • Samuel K. Y. Sung
چکیده

Kohonen’s self-organising map is used to identify the colour development of baked goods from samples taken during baking. The resulting bake curves represent the colours characteristic of a particular baked product. Images of baked goods can be segmented and foreign bodies identified using these baking curves.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Segmentation of Bake Images by a Self-Organising Map

A technique for segmentation of images of baked good is presented. The technique employs a Self-Organising Map to identify the characteristic colour development curve (bake curve) for each product. Segmentation is based upon the colour information contained in the bake curve. The technique is trained with only positive exemplars of the product.

متن کامل

Baked Product Classiication with the Use of a Self-organising Map

Study of the baking of biscuits involves among other aspects detailed analysis of colour changes in the product during the process. Previous study has shown the existence of a colour development curve (known as the baking curve) by examining colour development in the RGB and HSI colour spaces. In the current work a diierent approach to extracting the baking curve is presented. Using a Kohonen s...

متن کامل

Objective Bake Assessment Using Image Analysis and Artificial Intelligence

Bake assessment in food manufacture is currently performed by trained human inspectors. The subjective nature of human assessment introduces short-term variation and long-term drift of bake standards due to inconsistencies in human performance. A durable, repeatable and transferable assessment method is desirable to ensure long-term consistency of product bake and to facilitate product migratio...

متن کامل

A Method for Body Fat Composition Analysis in Abdominal Magnetic Resonance Images Via Self-Organizing Map Neural Network

Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...

متن کامل

Computing with Biologically Inspired Neural Oscillators: Application to Colour Image Segmentation

This paper investigates the computing capabilities and potential applications of neural oscillators, a biologically inspired neural model, to grey scale and colour image segmentation, an important task in image understanding and object recognition. A proposed neural system that exploits the synergy between neural oscillators and Kohonen self-organising maps (SOMs) is presented. It consists of a...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1998