Edge detection is a demanding need in robotic, military and automation areas and is used as an early image processing in high level image processors such as movement detectors, target tracker and etc. A typical technique for edge detection is the use of sensor-processor combination. In this combination raw images data are transferred to processor through a data line. This creates a bottleneck that reduces process speed. Due to the existence of this bottleneck, running real-time software edge detection requires very high speed processors that tend to be power consuming. An attractive solution to this problem is to shift part of the image data processing into the sensor hardware structure. It is done by designing and allocating some proper circuitry around image sensors to perform some early pixel-level image processing within the photo-sensor array. Intelligent vision chips as a new generation of image processing systems by combining image sensor and processing circuits in a single chip provide the opportunity for parallel data processing with higher speed and lower power consumption. Also due to the integration of these systems, area consumption will be reduced. In this work a kind of vision chip that has the ability of real-time edge detection has been designed and simulated in CMOS 180nm technology. The chip can recognize color and intensity edges by comparing color and intensity data of each pixel with neighboring pixels. It produces a two-bit result for each pixel which represents the type and the existence or absence of the edge in that pixel and hence provide the next processing stage with le requirement i term of computational power, cost, portability and power consummation. To implement the system, the mechanisms of biological vision systems in color, intensity and edge detections are studied; and the proposed detector has been designed based on retina models in color and edge detections. Buried Triple Junction photo detector (BTJ) is used as the pixel light sensing element. Color and intensity detections are done with only one BTJ by using the color filtering feature of silicon. The sensor determines three components of color that are used for both color and intensity detections. With this technique, the system is compact, the power requirement is reduced, and the chip is implementable in a standard CMOS technology with no extra processes. Light input dynamic range has been improved by using logarithmic amplifiers in the input stage of each pixel. The designed system has 80um*60um pixels, consumes 135nw power per pixel, and works with 1v power supply. It can be used in portable systems. System functionality has been verified through simulations. The results show that system can process image streams with up to 30 frames per second speed in real-time. Also they show that intensity edge detector has only high sensitivity to light intensity and has low sensitivity to light color and typically detects only intensity edges. Similarly simulation results show that color edge detector has good sensitivity to color changes and detects color edges if only one color component changes in a pixel place. The physical layout level of the design and post layout simulations have been presented in CMOS 180nm technology. Keywords edge detection, intelligent vision chips, biological vision systems, color detection, low-power circuits.